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NPI Product Engineer - AI Compute Hardware
WHAT MATX IS BUILDING MatX is building next-generation AI compute infrastructure for large-scale LLM training and inference. We’re looking for an experienced NPI Product Engineer to serve as the technical bridge between engineering and manufacturing. This includes owning product readiness, qualification, and quality as our AI chip, compute tray, and rack-scale platform moves from design into production. You’ll work closely with hardware, mechanical, systems, test, supply chain, quality, and manufacturing teams to ensure complex hardware products are built correctly, qualified on schedule, and ready to scale. WHAT YOU'LL DO HERE - Own product NPI from EVT through DVT and PVT, driving product readiness, quality, and schedule at each stage gate, and lead first article inspections, qualification reviews, and manufacturing readiness reviews with JDM/ODM partners - Partner with hardware, mechanical, electrical, systems, and program management to define product requirements, specifications, acceptance criteria, and NPI exit criteria, and resolve product-level DFM/DFT/DFA issues - Develop and drive product validation and qualification plans (functional, system-level, environmental, and reliability testing), and coordinate component qualification with hardware engineering and supply chain - Serve as the technical interface between engineering and JDM/ODM partners, ensuring requirements and design intent are correctly translated into manufacturing and test coverage - Drive product quality and yield improvement by analyzing defect trends and metrics (defect rate, first-pass yield, reliability), identifying root causes, and coordinating corrective actions - Own product-level ECO evaluation and implementation, and drive product readiness for transition from NPI to mass production, ensuring functionality, quality, reliability, and manufacturability - Maintain NPI product documentation (specifications, qualification reports, validation plans, test procedures, quality records) and communicate product risks, technical issues, and readiness to engineering and leadership WHO YOU ARE - 5+ years of NPI or hardware product engineering experience (PCB, server, AI compute, networking, or electronics hardware), with a proven track record introducing complex products through EVT, DVT, and PVT with JDM/ODM or contract manufacturers - Strong understanding of the hardware product development lifecycle from design through validation, qualification, and production ramp including DFM, DFT, and DFA for complex electronic assemblies - Experience defining and executing product validation and qualification plans (functional, system-level, environmental, and reliability testing) and tracking quality metrics such as defect rate, first-pass yield, and reliability - Experience analyzing product defects, yield data, and field/manufacturing failures, driving root cause analysis and corrective actions - Experience working directly with JDM/ODM partners on product reviews, qualification, issue resolution, and production readiness - Strong understanding of BOM management, ECO processes, component qualification, and product configuration control, with familiarity with PLM tools such as Arena or Agile - Strong cross-functional collaboration and communication skills, able to work across hardware, mechanical, supply chain, test, manufacturing, and program management, and present product status, risks, and quality data to leadership BONUS POINTS - Experience with high-power AI accelerators, GPU servers, or custom ASIC product introduction - Familiarity with liquid cooling system qualification and assembly - Experience with OCP Open Rack platform qualification, including data center rack integration and system-level product qualification - Knowledge of IPC standards (IPC-A-610, IPC-6012, IPC-7711/7721) - Familiarity with JTAG, ICT, or boundary scan methodologies - Experience with statistical process control and process capability analysis - Background in reliability engineering, including FMEA, accelerated life testing, and reliability qualification COMPENSATION The US base salary for this full-time position is determined based on a variety of factors including role, experience, location, job-related skills, and relevant education and training. Career length is only a guideline for compensation. - Early Career - $160,000 - $275,000 + equity - Mid Career - $175,000 - $400,000 + equity - Senior Career - $250,000 - $600,000 + equity What We Offer - Time off: 4 weeks PTO (accrued) + 12 company Holidays + up to 3 weeks remote work - Health: Company-subsidized Medical (Kaiser or Anthem) for employees & dependents, Guardian Dental and Vision insurances for employee & dependents, and life insurance (employee only), plus HSA and FSA offerings via Lively. - Financial Security: Choose from Roth or pre-tax 401K (or both) with a 5% company contribution (even if you don't contribute), 100% company-paid life insurance (up to $300K), long-term disability and travel insurance. - Professional Development: $1500 per year Professional Development Budget - Team Meals: MatX provides onsite team lunch & dinner Monday - Friday, with your choice of ordering via WeBox, Specialty’s or via our reimbursement system - Commute on Us: We pay 100% for your daily commute. Commute via our company rideshare account, reimburse public transportation, or get a Fasttrak card (or all three) - MatX E[x]tras: $50/mo to use on the perk you value most - Cell & Internet Reimbursement: $35/mo for cellular and $40/mo for wifi - Remote Home Setup: Use our Amazon business account for up to $1000 in office setup purchases. - Mental Wellbeing: 100% paid mental health benefit via SpringHealth and Guardian EAP. - Support to Parents: Up to 12 weeks paid parental leave regardless of path to parenthood, 10 weeks pregnancy disability leave, flexible return-to-work hours, and a $6K Family Fund to cover fertility, surrogacy, adoption, menopausal health, preservation, family counseling and more. As part of our dedication to the diversity of our team and our focus on creating an inviting and inclusive work experience, MatX is committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, gender, gender identity, gender expression, sexual orientation, age, physical or mental disability, medical condition, marital/domestic partner status, military and veteran status, genetic information or any other legally recognized protected basis under federal, state or local laws, regulations or ordinances. --------- This position requires access to information that is subject to U.S. export controls. This offer of employment is contingent upon the applicant's capacity to perform job functions in compliance with U.S. export control laws without obtaining a license from U.S. export control authorities. -------- MatX does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or People team and any resumes submitted are deemed to be the property of MatX.
Emulation Engineer
What MatX Is Building MatX is on a mission to be the compute platform for AGI. We are developing vertically integrated full-stack solutions from silicon to systems including hardware and software to train and run the largest ML workloads for AGI. MatX is seeking Emulation engineers to join our team as we create best-in-class silicon for high-performance and sustainable GenAI. Successful candidates for these roles will be responsible for delivering performant and functionally accurate silicon for MatX products across compute, memory management. High-speed connectivity and other key technologies. We're hiring a Senior/Staff Emulation Engineer to build the infrastructure, flows, and debug methodology behind our advanced connectivity SoCs. The role sits in the Emulation team, but the impact is broader: you'll create reusable flows that span emulation, SoC simulation, firmware/software bring-up, and post-silicon validation. We're looking for a multi-disciplinary engineer with an out-of-the-box, can-do mindset — someone who sees a gap and builds the bridge, comfortable moving between RTL, software, tooling, system debug, and vendor flows. You don't need to be an expert in every area listed below. You do need a reuse-first mindset, strong software instincts, and the ability to learn quickly across boundaries. What You'll Do Here - Define and execute emulation strategy and test plans for complex connectivity SoCs. - Bring up and debug large-scale models on commercial emulation platforms such as Cadence Palladium, Zebu or Veloce. - Integrate external components such as SpeedBridge and VirtualBridge adapters, Accelerated VIP, and memory models — for PCIe, HBM4, Ethernet, AXI/AMBA, JTAG, and (Q)SPI. And build custom transactors where needed. - Develop HW/SW co-emulation and co-simulation flows using RTL, software/reference models (Rust, C/C++, SystemC), firmware, and software tests. - Build reusable transactors, agents, stubs, bridges, checkers, and acceleration flows — including developing new transactors and agents from scratch when off-the-shelf options don't fit. - Drive emulation speed-ups and resource utilization — compile-time reduction, partitioning, clocking strategy, regression scheduling, multi-user capacity, and waveform/trace management. - Build automation for regression triage, debug, model usability, and engineering productivity. - Go beyond prompting with AI — build practical LLM-based tooling for log analysis, waveform triage, debug assistance, and flow generation, including custom skills, agents, rules, and workflows that fit our engineering stack. - Collaborate with architecture, RTL, DV, SoC, firmware, driver, kernel, validation, and EDA/vendor teams. Who You Are - Strong hands-on experience with SoC emulation or system-level validation. - Experience with at least one commercial emulation platform, such as Palladium. - Working Verilog/SystemVerilog and waveform-debug skills — enough to develop a custom transactor or agent when needed (with or without AI assistance). Deep RTL design expertise is not required. - Strong software and automation skills — Python plus one or more of C, C++, Rust, Tcl, or shell. - Demonstrated ability to build tools and infrastructure, not just run existing flows. - Strong system-level debug instincts spanning RTL, firmware, and software. - Ability to work independently and across functional and team boundaries. Bonus Points If You Have - UVM or hybrid SoC testbench development. - Integrating cycle-accurate, software, or reference models into emulation/DV flows. - Rust in verification or emulation flows (or strong interest in adopting it). - Bazel or large-scale build/regression systems. - Reusable stimulus across simulation, emulation, and post-silicon. - AI/LLMs used to build real engineering tools — debug, triage, flow generation — beyond chat prompting. - Connectivity SoCs, PCIe/CXL, Ethernet, DMA, HBM/memory subsystems, chiplets, or interconnect fabrics. - Firmware or driver bring-up on emulation platforms. - Scaling emulation or verification infrastructure across multiple projects or product lines. Compensation The US base salary for this full-time position is determined based on a variety of factors including role, experience, location, job related skills, and relevant education and training. Career length is only a guideline for compensation. - Early Career - $160,000 - $275,000 + equity - Mid Career - $175,000 - $400,000 + equity - Senior Career - $250,000 - $600,000 + equity What We Offer - Time off: 4 weeks PTO (accrued) + 12 company Holidays + up to 3 weeks remote work - Health: Company-subsidized Medical (Kaiser or Anthem) for employees & dependents, Guardian Dental and Vision insurances for employee & dependents, and life insurance (employee only), plus HSA and FSA offerings via Lively. - Financial Security: Choose from Roth or pre-tax 401K (or both) with a 5% company contribution (even if you don't contribute), 100% company-paid life insurance (up to $300K), long-term disability and travel insurance. - Professional Development: $1500 per year Professional Development Budget - Team Meals: MatX provides onsite team lunch & dinner Monday - Friday, with your choice of ordering via WeBox, Specialty’s or via our reimbursement system - Commute on Us: We pay 100% for your daily commute. Commute via our company rideshare account, reimburse public transportation, or get a Fasttrak card (or all three) - MatX E[x]tras: $50/mo to use on the perk you value most - Cell & Internet Reimbursement: $35/mo for cellular and $40/mo for wifi - Remote Home Setup: Use our Amazon business account for up to $1000 in office setup purchases. - Mental Wellbeing: 100% paid mental health benefit via SpringHealth and Guardian EAP. - Support to Parents: Up to 12 weeks paid parental leave regardless of path to parenthood, 10 weeks pregnancy disability leave, flexible return-to-work hours, and a $6K Family Fund to cover fertility, surrogacy, adoption, menopausal health, preservation, family counseling and more. As part of our dedication to the diversity of our team and our focus on creating an inviting and inclusive work experience, MatX is committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, gender, gender identity, gender expression, sexual orientation, age, physical or mental disability, medical condition, marital/domestic partner status, military and veteran status, genetic information or any other legally recognized protected basis under federal, state or local laws, regulations or ordinances. --------- This position requires access to information that is subject to U.S. export controls. This offer of employment is contingent upon the applicant's capacity to perform job functions in compliance with U.S. export control laws without obtaining a license from U.S. export control authorities. -------- MatX does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or People team and any resumes submitted are deemed to be the property of MatX.
AI Silicon Architect
What MatX Is Building MatX designs hardware tailored for the world’s best AI models. Our hardware will make a given level of intelligence available 3-5 years sooner. We are developing vertically integrated full-stack solutions from silicon to systems including hardware and software to train and run the world’s largest models. MatX is seeking an Architect to join our team as we create best-in-class silicon for high-performance and sustainable GenAI. The successful candidate for this role will be responsible for delivering performant silicon architecture at the full-chip or subsystem level. What You'll Do Here - Develop, support, and own hardware architecture throughout the product lifecycle - Deeply understand customer use cases, workload performance, and ML systems research - Produce requirements and architecture specifications - Estimate hardware area, timing, and power to inform architectural trade-offs - Collaborate closely with Research, Software, and Hardware teams - Interface with vendors and customers - Architectural Responsibilities May Include: - Parallel Compute: SIMD, Vector, VLIW, and other parallel execution models - Data Movement: Efficient storage and communication across memory and network fabrics - Distributed Systems: Workload mapping, bottleneck analysis, and scalable distributed systems Who You Are - Expertise in modern high-performance CPU, GPU, or AI accelerator architecture and hardware/software interactions - Experience analyzing and optimizing system performance using diverse tools and methodologies - Proficiency in programming and code optimization - Excellent writing skills - This is a hybrid role that will require you to work from our Mountain View, CA office 3 days a week on Tuesday through Thursday Compensation The US base salary for this full-time position is determined based on a variety of factors including role, experience, location, job related skills, and relevant education and training. Career length is only a guideline for compensation. - Early Career - $160,000 - $275,000 + equity - Mid Career - $175,000 - $450,000 + equity - Senior Career - $275,000 - $600,000 + equity What We Offer - Time off: 4 weeks PTO (accrued) + 12 company Holidays + up to 3 weeks remote work - Health: Company-subsidized Medical (Kaiser or Anthem) for employees & dependents, Guardian Dental and Vision insurances for employee & dependents, and life insurance (employee only), plus HSA and FSA offerings via Lively. - Financial Security: Choose from Roth or pre-tax 401K (or both) with a 5% company contribution (even if you don't contribute), 100% company-paid life insurance (up to $300K), long-term disability and travel insurance. - Professional Development: $1500 per year Professional Development Budget - Team Meals: MatX provides onsite team lunch & dinner Monday - Friday, with your choice of ordering via WeBox, Specialty’s or via our reimbursement system - Commute on Us: We pay 100% for your daily commute. Commute via our company rideshare account, reimburse public transportation, or get a Fasttrak card (or all three) - MatX E[x]tras: $50/mo to use on the perk you value most - Cell & Internet Reimbursement: $35/mo for cellular and $40/mo for wifi - Remote Home Setup: Use our Amazon business account for up to $1000 in office setup purchases. - Mental Wellbeing: 100% paid mental health benefit via SpringHealth and Guardian EAP. - Support to Parents: Up to 12 weeks paid parental leave regardless of path to parenthood, 10 weeks pregnancy disability leave, flexible return-to-work hours, and a $6K Family Fund to cover fertility, surrogacy, adoption, menopausal health, preservation, family counseling and more. As part of our dedication to the diversity of our team and our focus on creating an inviting and inclusive work experience, MatX is committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, gender, gender identity, gender expression, sexual orientation, age, physical or mental disability, medical condition, marital/domestic partner status, military and veteran status, genetic information or any other legally recognized protected basis under federal, state or local laws, regulations or ordinances. --------- This position requires access to information that is subject to U.S. export controls. This offer of employment is contingent upon the applicant's capacity to perform job functions in compliance with U.S. export control laws without obtaining a license from U.S. export control authorities. -------- MatX does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or People team and any resumes submitted are deemed to be the property of MatX.
AI Chip Architect
What MatX Is Building MatX designs hardware tailored for the world’s best AI models. Our hardware will make a given level of intelligence available 3-5 years sooner. We are developing vertically integrated full-stack solutions from silicon to systems including hardware and software to train and run the world’s largest models. MatX is seeking an Architect to join our team as we create best-in-class silicon for high-performance and sustainable GenAI. The successful candidate for this role will be responsible for delivering performant silicon architecture at the full-chip or subsystem level. MatX is seeking an AI Accelerator Compute Architect to help define the compute architecture for our next-generation GenAI accelerators. WHAT YOU'LL DO - Define the architecture for MatX’s AI compute subsystem, including ISA, connectivity, memories, and control.. - Derive architectural requirements from AI use cases. - Conduct analytical and empirical performance analysis. - Collaborate closely with Research, SW, and HW teams to ensure we architect just-right silicon for workloads, programmability, and PPA. - Work through power, area, performance tradeoffs with stakeholders. - Support test plan reviews, first-silicon bring-up, and post-silicon debug. WHO YOU ARE - Strong background in computer architecture, especially AI accelerators, GPUs, TPUs, vector processors, SIMD, VLIW, or other parallel compute architectures. - Experience translating workloads into hardware architecture. - Solid microarchitecture fundamentals. - First-principles understanding of latency, throughput, utilization, and scalability. - Familiarity with numeric formats, quantization, rounding, and precision/performance tradeoffs. - Programming, code optimization, or kernel-level performance analysis experience. - Excellent written and verbal communication skills. - Familiarity with performance-optimization techniques in large-scale transformer models is a plus. WORK LOCATION This is a hybrid role based in our Mountain View, CA office, with in-office work Tuesday through Thursday. In exceptional cases, remote work arrangements may be considered. COMPENSATION The US base salary for this full-time position is determined based on a variety of factors including role, experience, location, job related skills, and relevant education and training. Career length is only a guideline for compensation. - Early Career - $160,000 - $275,000 + equity - Mid Career - $175,000 - $450,000 + equity - Senior Career - $275,000 - $600,000 + equity What We Offer - Time off: 4 weeks PTO (accrued) + 12 company Holidays + up to 3 weeks remote work - Health: Company-subsidized Medical (Kaiser or Anthem) for employees & dependents, Guardian Dental and Vision insurances for employee & dependents, and life insurance (employee only), plus HSA and FSA offerings via Lively. - Financial Security: Choose from Roth or pre-tax 401K (or both) with a 5% company contribution (even if you don't contribute), 100% company-paid life insurance (up to $300K), long-term disability and travel insurance. - Professional Development: $1500 per year Professional Development Budget - Team Meals: MatX provides onsite team lunch & dinner Monday - Friday, with your choice of ordering via WeBox, Specialty’s or via our reimbursement system - Commute on Us: We pay 100% for your daily commute. Commute via our company rideshare account, reimburse public transportation, or get a Fasttrak card (or all three) - MatX E[x]tras: $50/mo to use on the perk you value most - Cell & Internet Reimbursement: $35/mo for cellular and $40/mo for wifi - Remote Home Setup: Use our Amazon business account for up to $1000 in office setup purchases. - Mental Wellbeing: 100% paid mental health benefit via SpringHealth and Guardian EAP. - Support to Parents: Up to 12 weeks paid parental leave regardless of path to parenthood, 10 weeks pregnancy disability leave, flexible return-to-work hours, and a $6K Family Fund to cover fertility, surrogacy, adoption, menopausal health, preservation, family counseling and more. As part of our dedication to the diversity of our team and our focus on creating an inviting and inclusive work experience, MatX is committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, gender, gender identity, gender expression, sexual orientation, age, physical or mental disability, medical condition, marital/domestic partner status, military and veteran status, genetic information or any other legally recognized protected basis under federal, state or local laws, regulations or ordinances. --------- This position requires access to information that is subject to U.S. export controls. This offer of employment is contingent upon the applicant's capacity to perform job functions in compliance with U.S. export control laws without obtaining a license from U.S. export control authorities. -------- MatX does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or People team and any resumes submitted are deemed to be the property of MatX.
Solutions Architect
ABOUT LIQUID AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. THE OPPORTUNITY Liquid AI is building a solutions architecture function from scratch. You will be one of the first SAs, working directly with the Head of Solutions Architecture and across the go-to-market org to own customer engagements end-to-end. Our models are purpose-built for environments where memory, latency, and power are binding constraints - edge devices, mobile, embedded systems, and on-prem infrastructure where frontier models simply cannot run. You will work at this boundary every day. Customers range from AI-native companies to enterprise organizations exploring AI for the first time. Your job is to bridge the gap between what our models can do and what customers believe is possible, then deliver on that promise from technical validation through go-live. WHAT WE'RE LOOKING FOR We need someone who: - Technical builder: You can download a model, build a demo, and present it to a customer. You are as comfortable in a Jupyter notebook as you are in a boardroom. - Creative problem solver: You see opportunities where customers see limitations. You can take a small, efficient model and show an enterprise why it changes their cost structure or enables something they did not think was possible. - End-to-end owner: You do not draw a line between 'pre-sales' and 'post-sales.' You own the outcome from first call to go-live and beyond. - Org builder: You want to build a function, not inherit one. You will create playbooks, demo libraries, and engagement processes that scale as the team grows. - Imagination-gap closer: Enterprise buyers often cannot envision what a fine-tuned small model can do at middleware speeds. You don't just demo—you reframe what's possible on hardware they already own. THE WORK - Own customer engagements end-to-end: from qualified opportunity through technical validation, go-live, and ongoing delivery across all customer segments - Build customer-specific demos and proofs-of-concept using Liquid models (including LEAP for fine-tuning, domain adaptation, and evaluation) to drive technical wins - Lead technical discovery: map current-state customer architectures to Liquid solutions, drive competitive positioning against open-source and incumbent models, and quantify ROI for both cost-optimization and new-experience use cases - Co-own the product-field feedback loop: document friction patterns, eval failures, and capability gaps from engagements and partner with product and research to influence roadmap - Turn engagement learnings into reusable assets: reference architectures, solution primitives, demo building blocks, engagement playbooks, and vertical-specific solution patterns across Liquid's priority industries DESIRED EXPERIENCE Must-have: - Applied ML skills: hands-on experience working with ML models in customer-facing contexts (building demos, prototypes, or production integrations) - Pre-sales and post-sales experience: you have owned technical customer engagements end-to-end, not just the pitch - Strong customer-facing communication: you can run discovery, build relationships with technical and business buyers, and present to executives - Understanding of AI architectures and deployment tradeoffs: token efficiency, on-device vs. cloud, model size vs. latency, open-weight vs. proprietary Nice-to-have: - Familiarity with small or efficient model deployment (edge, on-device, latency-constrained environments) - Track record of creating thought leadership content, technical blogs, or presenting at industry events - Familiarity with efficient model deployment: quantization (INT4/INT8, GGUF, AWQ), model serving frameworks (vLLM, TensorRT-LLM, llama.cpp), and hardware-aware optimization for edge or latency-constrained environments - Experience designing and debugging model evaluations—you understand why benchmark results can diverge from production performance and know how to diagnose the root cause WHAT SUCCESS LOOKS LIKE (YEAR ONE) 1. Qualified opportunities convert to technical wins faster, with a measurable improvement in the qualified-to-win rate 2. A library of scalable demos, engagement playbooks, and customer-facing collateral exists and is actively used 3. A structured feedback loop from customer conversations to the product and model teams is established and influencing roadmap decisions WHAT WE OFFER - Build the function: You are defining how Liquid goes to market technically, with direct influence on product direction and access to the founding team. - Compensation: Competitive base salary with equity in a unicorn-stage company - Health: We pay 100% of medical, dental, and vision premiums for employees and dependents - Financial: 401(k) matching up to 4% of base pay - Time Off: Unlimited PTO plus company-wide Refill Days throughout the year
Product Manager
ABOUT LIQUID AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. THE OPPORTUNITY We're hiring a Product Manager to drive specific product bets from idea to product-market fit. This is a hands-on, ground-level role: you own an experiment, or a small set of them, get the product into real users' hands, and iterate toward PMF, working shoulder to shoulder with our ML, inference, and engineering teams to turn their energy into crisp, executable direction. It is not a traditional SaaS PM role: the model and the product are inseparable, our core offering is customization & fine-tuning rather than prompt-only use, and real model depth is a prerequisite. WHAT WE'RE LOOKING FOR We need someone who: - Focus-giver: You turn high-energy, unfocused ideas into tight, executable product direction that engineers can build against. - Evidence over intuition: You put products in front of real users early and let honest feedback drive decisions. - Technically fluent and AI-native: You hold your own with ML and inference engineers, know when an LFM is the right tool, and use AI & coding tools to prototype and test hypotheses yourself. - Conviction without stubbornness: You hold a clear point of view, update it in light of evidence, and can hit the ground running with light support. THE WORK - Own one or more active product experiments end-to-end and drive them toward product-market fit. - Turn vague, high-energy ideas into tight, executable product requirements that engineers can build against. - Put the product in real users' hands early, gather genuine feedback, and iterate. - Ruthlessly prioritize: decide what to build now, what to defer, and what to kill. - Work closely with ML, inference, and engineering teams, and flex across bets as priorities shift. DESIRED EXPERIENCE Must-have: - Direct, hands-on ML or applied LLM experience: you have built or trained models, you know the difference between prompting and fine-tuning in practice, and you know when an LFM is the right tool. - A strong bias for action: you use AI and coding tools to prototype and test hypotheses yourself, so your insights are higher-signal than a PM who ran deep research once. - Demonstrated ownership of product direction and prioritization, not just execution against a handed-down roadmap. - The ability to turn an ambiguous idea into a concrete, buildable plan, with light support rather than heavy coaching. Nice-to-have: - Enterprise product expertise: the focus and execution it takes to bring a new enterprise product to market and win in enterprise. - Experience at an AI/ML company or on AI-powered products. - Familiarity with edge or on-device inference, agentic harnesses, evals, or observability. WHAT SUCCESS LOOKS LIKE (YEAR ONE) 1. You own a bet end to end and take it from an ambiguous opportunity to a validated, or confidently killed, product direction backed by real user evidence. 2. The engineers you support move faster because your requirements are crisp and well-prioritized. 3. You have established a repeatable way to get products in front of users and turn their feedback into decisions. WHAT WE OFFER - Focused ownership: You drive a product bet end to end rather than owning a sliver of a large platform. - Compensation: Competitive base salary with equity in a unicorn-stage company. - Health: We pay 100% of medical, dental, and vision premiums for employees and dependents. - Financial: 401(k) matching up to 4% of base pay. - Time Off: Unlimited PTO plus company-wide Refill Days throughout the year.
Member of Technical Staff - Multi-Modal, Audio
ABOUT LIQUID AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. THE OPPORTUNITY Our Audio team is building frontier speech-language models that handle STT, TTS, and speech-to-speech in a single architecture. This role sits at the center of applied audio model development, working directly with the technical lead to ship production systems that run on-device under real-time constraints. You will own critical workstreams across data pipelines, evaluation systems, and customer deployments. If you want high ownership on rare technical problems in a small, elite team where your code ships, this is the role. WHAT WE'RE LOOKING FOR We need someone who: - Builds first, theorizes later: You ship working systems, not just notebooks. Production-grade code is your default, not a stretch goal. - Owns outcomes end-to-end: From data pipelines to customer deployments, you take responsibility for the full stack without waiting for someone else to handle the hard parts. - Thrives under constraints: On-device, low-latency, memory-limited systems excite you. You see constraints as design parameters, not blockers. - Ramps quickly on new territory: Gaps in specific subdomains are fine if you close them fast. You seek out feedback and stay focused on what moves the needle. THE WORK - Build and scale data pipelines for audio model training, including preprocessing, augmentation, and quality filtering at scale - Design, implement, and maintain evaluation systems that measure multimodal performance across internal and public benchmarks - Fine-tune and adapt audio models for customer-specific use cases, owning delivery from requirements through deployment - Contribute production code to the core audio repository, collaborating with infrastructure and research teams - Support experimentation under real hardware constraints, shifting between customer work and core development as priorities evolve DESIRED EXPERIENCE Must-have: - Strong programming fundamentals with demonstrated ability to write clean, maintainable, production-grade code - Experience building and shipping production ML systems beyond model training (data pipelines, evals, serving infrastructure) - Proficiency in PyTorch and familiarity with distributed training frameworks (DeepSpeed, FSDP, or similar) - Track record of collaborating effectively in shared codebases with high engineering standards Nice-to-have: - Direct experience with audio/speech models (ASR, TTS, vocoders, diarization, or speech-to-speech systems) - Experience designing and running large-scale training experiments on distributed GPU clusters - Open-source contributions that demonstrate code quality and engineering judgment WHAT SUCCESS LOOKS LIKE (YEAR ONE) - Within 6 months, you independently deliver production-ready data pipelines or evaluation systems and own at least one customer workstream end-to-end - Your PRs to the core audio repo are accepted without heavy rework, demonstrating strong judgment in system design - By year end, you operate as a second pillar to the technical lead, unblocking parallel workstreams and raising overall team velocity WHAT WE OFFER - Rare technical problems: Work on audio-to-audio frontier systems with real ownership in a team small enough that your contributions ship directly to production. - Compensation: Competitive base salary with equity in a unicorn-stage company - Health: We pay 100% of medical, dental, and vision premiums for employees and dependents - Financial: 401(k) matching up to 4% of base pay - Time Off: Unlimited PTO plus company-wide Refill Days throughout the year
Senior/Principal ML Scientist, Translational Biolo...
Your Impact at LILA Lila is redefining the future of biomedicine by combining large-scale automated data generation with scientific superintelligence. We are building the loop where AI, automation, and experimental biology co-evolve. We are seeking a Senior ML Scientist to connect that work to human medicine, building the systems that assess whether a clinical program's biology holds up. Three questions define the work. Is the mechanism well supported? What has actually been established about how this intervention is meant to work, and what has only been assumed. Does the mechanism operate in patients? Human genetics, expression, cohort and prior-trial evidence all bear on whether the biology that works in a model system is present, and rate-limiting, in the population being treated. Is the trial built for that mechanism? Endpoints that read out the right thing on the right timescale, biomarkers that measure what the mechanism actually does, and enrollment criteria that select patients in whom it is operative — or, very often, none of these. You will not answer these program by program yourself. You will build the systems that do it, drawing on the mechanistic models and structured biological evidence the rest of the group generates, and grounding them in human data. Your own judgment is the specification and the standard those systems are held to, and you will build the evaluations — including forecasts of real program outcomes scored against what was knowable at the time — that tell you whether they are any good. What You'll Be Building - Build systems that assess mechanistic support for a clinical program. Take the structured biological evidence and mechanistic models generated elsewhere in the group and turn them into an assessment of whether an intervention's proposed mechanism is established, assumed, or unexamined. - Ground mechanism in human data. Analyze human genetic, expression, cohort and trial-derived evidence to determine whether a mechanism is present, active and rate-limiting in the relevant patient population — and how heterogeneous it is across that population. - Assess trial design against mechanism. Evaluate endpoint choice and timing, biomarker definition and assay, dose and schedule, and eligibility and enrichment criteria for alignment with the proposed mechanism, and encode that assessment so it can be applied at scale rather than case by case. - Build the evaluations that hold these systems to account, including outcome-verifiable forecasts of real program progression scored using only information available at the prediction date, with the evidence boundary enforced against contamination. Run them yourself and report honestly when a contribution adds nothing. - Co-design with ML scientists, mechanism scientists and engineers, translate model output into decisions people actually make, and publish — what is and is not predictable from mechanistic and human evidence is a real scientific question we intend to answer in public. - Communicate findings clearly to technical and cross-functional audiences, including scientists, engineers, product partners, and therapeutic stakeholders. - Support external scientific visibility through publications, presentations, and engagement with ML/AI for Biology, computational biology and therapeutic discovery communities, as appropriate. What You'll Need to Succeed - PhD in a computational discipline — translational bioinformatics, computational biology, biomedical informatics, biostatistics, epidemiology, machine learning, or related — with research centered on human biomedical data. - Hands-on ML and data analysis for translational medicine. Fluent Python; substantial experience analyzing human genetic, multi-omic, cohort, trial or real-world data in reproducible pipelines. You will run your own analyses and evaluations and interpret them yourself. - Mechanistic reasoning about therapeutic interventions. Able to state how an intervention is meant to work, what evidence would establish each step, and where human evidence supports or undercuts it. - Clinical development fluency. Working knowledge of trial design, endpoints, biomarker strategy, eligibility and enrichment — enough to read a protocol and judge whether it tests the mechanism it claims to. - Evidence judgment and a systems instinct. Able to reason about what was knowable when and resist hindsight — and interested in making that judgment reproducible by something other than you, through structure and evaluation rather than case-by-case expertise. Bonus Points For - Experience with human genetics for target identification and validation — common and rare variant evidence, QTL and expression data, or genetically supported target work. - Experience with biomarker development, patient stratification, companion diagnostics, or enrichment strategy. - Experience with clinical trial datasets, real-world data, or observational cohort analysis, and their known limitations. - Experience evaluating language models or agents on scientific judgment tasks, including contamination and memorization controls. - Familiarity with survival analysis, competing risks, calibration, or forecasting methodology. - Experience with structured evidence frameworks — GRADE, systematic review protocols, or bespoke assessment rubrics. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $268,000 - $384,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Research Product Manager, Post Training
Your Impact at LILA Lila’s foundational models are the engine behind scientific superintelligence. We are looking for a Research Product Manager to set the vision for what Lila’s foundational models can achieve next - defining the capabilities and performance that turn breakthrough research into real-world scientific impact. In this role, you will own the capability roadmap for Lila’s core foundational model releases. You will synthesize signal from domain science teams, product, commercial opportunities, and the competitive model landscape into a clear, prioritized roadmap of model capabilities. Sitting at the seam between research ambition and real-world impact, your work will help ensure every model we ship is aimed at the capabilities that matter most, and that research moves into production with confidence. What You'll Be Building - Own the capability roadmap for Lila's core, foundational models: define and prioritize the specific capabilities each release should target, with an opinionated and defensible rationale for those choices. - Translate input from domain/science teams, the product organization, and commercial stakeholders into concrete, measurable model requirements that researchers can build against. - Perform ongoing analysis of competitive and frontier models - both general-purpose and scientific - turning benchmark results and capability gaps into roadmap decisions. - Define the evaluation criteria and success metrics that determine whether a target capability has actually been achieved. - Establish the gating criteria for promoting models to production. - Partner closely with research and model-training leads to sequence capability work realistically against compute, data, and timeline constraints. - Maintain transparent documentation of capability targets, evaluation results, and release decisions so the reasoning behind every model is auditable and easy to revisit. What You'll Need to Succeed - Bachelor's or Master's degree in Computer Science, Engineering, or a related field - or equivalent hands-on experience with AI/ML systems. - Proven product management experience for AI/ML products, ideally including ownership of a model, platform, or capability roadmap in a scientific domain. - A strong understanding of how foundational or large models are trained, evaluated, and released - with the ability to engage credibly with researchers and make sound prioritization calls. - A track record of translating stakeholder needs and competitive signal into clear, measurable requirements. - Experience defining release criteria and quality gates for a production system or model. - Excellent written and verbal communication, with a track record of driving cross-functional decisions. Bonus Points For - Product management experience with foundation models, frontier models, or AI platforms. - Experience working at an AI-first research organization or in life sciences or materials science. - Familiarity with model evaluation methodologies, benchmarking, and evaluation infrastructure. - Comfort operating in fast-moving, ambiguous, early-stage research environments. - Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $204,000 - $310,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Associate Director, App
Your Impact at LILA Scientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality — and we need engineering leaders who want to build the team that solves problems no one has solved before. We're hiring an Associate Director of Engineering, Application Team to lead the engineers designing the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI. About The Team The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results. - AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons. - The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them. - You'll lead engineers who learn domains they never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your team's technical surface area grows fast. - Your team ships things that matter. The tools they build accelerate research timelines from months to days. If you want to lead at the intersection of AI and science, move fast, and grow the kind of team that can architect systems that don't exist yet — we want to talk. What You'll Be Building - Team Leadership: Build, mentor, and manage a high-performing team of 8-10 engineers spanning full-stack, agent, and platform expertise. Foster a culture of collaboration, ownership, and continuous improvement; conduct performance reviews, provide feedback, and identify opportunities for growth. Manage team workload, prioritize projects, and ensure timely delivery of high-quality solutions. - Technical Strategy & Execution: Define and execute the technical roadmap for LILA's application layer aligning with LILA's broader AI and product strategy. Drive innovation in how scientists interact with AI-driven systems. - Product Delivery: Own end-to-end delivery of the application platform — chat, agents, artifacts, and the integrations connecting them to lab workflows and ML pipelines — ensuring reliability, performance, and security across everything the team ships. - Cross-Functional Collaboration: Partner with ML researchers, scientists, product managers, and other engineering leaders to understand scientific workflows and translate them into product capabilities. Communicate technical concepts effectively to both technical and non-technical audiences; manage expectations and ensure alignment across teams. - Engineering Thought Leadership: Represent LILA's applied-AI work externally through conferences, presentations, and writing — helping attract top talent and establishing LILA's leadership at the intersection of AI and science. What You'll Need To Succeed - Bachelor's or Master's degree in Computer Science, Engineering, or related field. - 12+ years of engineering experience building and deploying large-scale production systems, with 5+ years leading senior engineers. - Track record of building and growing high-performing engineering teams in high-growth or early-stage environments where speed-to-value mattered as much as long-term architecture. - Deep technical judgment on Applied AI (agents, MCP, context engineering) and across the full stack (React, TypeScript, Python, FastAPI, SQL/NoSQL, AWS, Kubernetes). - Hands-on experience — personally and on the teams you've led — using AI coding assistants and agentic tooling to drive productivity. - Proven ability to define technical strategy, drive it to execution, and balance trade-offs between scalability, performance, delivery speed, and maintainability. - Acute listening skills and a proven track record of partnering cross-functionally with scientists, ML engineers, product, and design; able to explain complex ideas to diverse audiences. Bonus Points For - Applied AI Engineering leadership: Experience shipping products built on AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks. - AI-native product intuition: A point of view on what "good" looks like for chat, agent, and copilot experiences — and how to evolve it as the underlying models improve. - Cloud & DevOps depth: Familiarity with AWS, Kubernetes, infrastructure-as-code (Terraform, CloudFormation), and CI/CD (GitHub Actions). - Thought leadership in the applied-AI community via conference talks, blog posts, or open source. - Scientific domain exposure: Experience with laboratory software, analytics for life sciences or material sciences, or adjacent scientific computing domains. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $204,000 - $306,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Senior Software Engineer, Agents
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. What We're Looking For The Agents team at Lightning AI is building the infrastructure that powers the next generation of AI applications. As AI agents move from prototypes to production, developers need reliable systems for orchestrating workflows, coordinating models, executing tools, and managing long-running state. Our goal is to provide the platform and abstractions that make building production-ready agentic applications as simple as deploying any modern software service. We're looking for a Senior Software Engineer to help design and build the backend systems that power Lightning AI's agent platform. You'll work on orchestration frameworks, tool execution, workflow management, memory and state handling, and developer-facing APIs that enable customers to build sophisticated AI applications with confidence. You'll partner closely with engineers across Core Platform, Training & Experimentation, Sandboxes, and Optimized Compute to deliver platform capabilities that are reliable, scalable, and intuitive for developers. This role is based in one of our San Francisco, NYC, or London office hubs, with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time. What You’ll Do - Design and build backend services that power AI agent orchestration and execution. - Develop scalable APIs and platform capabilities for tool use, workflow orchestration, memory, and state management. - Build reliable infrastructure that enables long-running, distributed AI workflows. - Partner with product, research, and platform engineering teams to bring new agent capabilities into production. - Improve platform reliability, observability, and performance as customer workloads continue to scale. - Evaluate and strengthen technical architecture, engineering processes, and developer tooling. - Maintain high standards for software quality through testing, automation, continuous delivery, and proactive management of technical debt. - Mentor engineers on system design, distributed systems, and backend engineering best practices What You’ll Need - Extensive experience building scalable backend systems using Go, Python, Rust, or similar languages. - Strong understanding of distributed systems, asynchronous processing, APIs, and cloud-native application architecture. - Experience designing and operating production services at scale. - Hands-on experience building backend platforms, developer tools, or infrastructure products. - Familiarity with cloud platforms such as AWS, GCP, or Azure and container technologies including Docker and Kubernetes. - Proven ability to take ownership of large technical initiatives from architecture through production. - Commitment to software quality, automated testing, observability, and continuous delivery. - Strong communication skills and the ability to collaborate effectively across engineering, product, research, and design teams. - Ability to thrive in fast-moving, ambiguous environments while balancing technical excellence with product impact. Compensation We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $180,000 - $250,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Senior Product Designer
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. What We're Looking For We are looking for a senior product designer to help us design groundbreaking technology that will transform the machine learning ecosystem and fundamentally change how the world experiences software. With a diverse skill set spanning product, interaction, and visual design, you are able to create products that are a joy to use and add tangible value to our users. You will collaborate across product and engineering to bring user flows and designs to life while working closely with users to test new ideas, conduct research, and gather feedback. You thrive in a fast-paced, start-up environment with a focus on speed, quality, and iteration from proof of concept to release. You will be joining the Design Team and report to our Chief Creative Officer. This is a hybrid role based in our New York City office with in-office requirements of 2 days per week. We are open to San Francisco but NYC is the preferred location. The salary range for this role is $160,000-$200,000. What You’ll Do - Collaborate with product and engineering teams to shape the user experience, interface, interactions, and visual design of new and existing features. Act as a key design partner in defining product strategy throughout the end-to-end development process. - Craft user journeys, flows, prototypes, and designs—sometimes starting from scratch, other times by refining early engineering prototypes or providing design enhancements and guidance as products evolve. - Proactively identify design opportunities and drive continuous improvement based on business objectives, user requirements, and customer requests. - Engage with the open source AI community and enterprise AI researchers and builders to understand real-world needs, workflows, and challenges—bringing those insights directly into the product design process. - Discover creative ways to eliminate friction and reduce papercuts through design, making it easier for users to onboard and utilize our platform from day one. - Advocate for scalable, user-centered design systems and processes that improve design velocity, consistency, and impact across the product. What You’ll Need - 5+ years of experience designing B2C software or technical platforms, preferably in developer tools, AI/ML, or SaaS environments - Strong portfolio showcasing end-to-end product thinking across UX, interaction, and visual design - Experience working with product managers, engineers, and researchers to iterate quickly and ship thoughtfully - Curiosity and initiative in engaging with the open source AI ecosystem, and a desire to understand the needs of both individual contributors and enterprise AI teams - Comfort working in ambiguity and across multiple product maturity levels—from early-stage prototypes to production features - Proficiency in Figma and modern design tools - Familiarity with technical concepts like machine learning, APIs, or cloud infrastructure (not required, but a plus) - Excellent communication skills, with the ability to present design rationale clearly and influence cross-functional teams - A mindset of continuous learning, user advocacy, and pragmatic design execution - Experience coding front-end is not required but a big plus! We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $160,000 - $200,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Partner Account Manager
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. Partner Account Manager Team: Partnerships / Channel Location: [NYC] - Hybrid Reports to: Head of Partnerships or VP, Channels About Lightning AI Lightning AI is building the platform and infrastructure that make it dramatically easier for teams to develop, train, deploy, and scale AI systems. As the company behind PyTorch Lightning, and following our merger with Voltage Park, we bring together developer-first AI tooling with high-performance compute infrastructure for researchers, startups, and enterprises building at the frontier of AI. We operate with a simple set of values: Move Fast, Focus, Balance, Craftsmanship, and Minimal. We care about people who can operate with urgency, solve hard problems directly, and build with high standards without creating unnecessary complexity. About the Role We are looking for a Partner Account Manager to help build Lightning AI’s partner ecosystem and turn strategic partnerships into real revenue. This role will own relationships with channel, cloud, reseller, services, and technology partners, and will be responsible for building joint pipeline, aligning field teams, and making partners successful in positioning Lightning AI to customers building serious AI systems. What You'll Do - Own a portfolio of strategic partners and build clear joint business plans tied to pipeline, revenue, customer adoption, and field engagement. - Create and execute co-selling motions with partner sales teams, Lightning AI Account Executives, Solutions Engineering, Marketing, and Customer Success. - Identify partner-sourced and partner-influenced opportunities, qualify fit, and help move deals through the sales cycle. - Develop partner account plans, executive alignment maps, target account lists, enablement plans, and quarterly business reviews. - Work with Channel MLSEs and Partner Enablement to ensure partner teams understand Lightning AI’s technical value proposition and how to identify strong-fit customers. - Negotiate and operationalize partner motions, including referral, resale, co-sell, marketplace, implementation, and services workflows where applicable. - Track partner performance, pipeline health, sourced revenue, influenced revenue, activation, and engagement quality. - Represent partner feedback internally and help improve partner programs, packaging, integrations, and field processes. What We're Looking For - 5+ years in partnerships, channel sales, business development, alliances, enterprise sales, or partner account management. - Experience building revenue-producing partnerships in technical B2B markets. - Strong commercial instincts and the ability to turn partner relationships into pipeline, opportunities, and closed revenue. - Experience working with sales teams, technical pre-sales teams, partner field teams, marketing, and operations. - Ability to build trust with partner executives and field sellers while driving accountability to measurable outcomes. - Strong project management and communication skills, especially in ambiguous or cross-company environments. - Comfort operating in a high-growth company where the partner motion is still being built. Nice-to-Haves - Experience with cloud partners, systems integrators, AI/ML consultancies, data partners, developer platforms, or infrastructure ecosystems. - Experience with marketplace, resale, referral, co-sell, or services partner models. - Familiarity with AI infrastructure, GPUs, MLOps, data platforms, or enterprise cloud buying cycles. - Experience building partner programs from an early stage. Why Lightning AI - You will help define how companies build and scale real AI systems, not just sell another generic software product. - You will work with technical customers and teammates who care about speed, clarity, craft, and direct problem-solving. - You will join a company with developer credibility, infrastructure ambition, and a GTM motion that is still early enough to shape. We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $175 - $200 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Infrastructure Operations Engineer (APAC)
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. *]:pointer-events-auto [content-visibility:auto] supports-[content-visibility:auto]:[contain-intrinsic-size:auto_100lvh] R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="request-WEB:6da214d3-9e35-4d43-89b6-34d5a76ffba7-1" data-turn-id-container="request-WEB:6da214d3-9e35-4d43-89b6-34d5a76ffba7-1" data-testid="conversation-turn-4" data-scroll-anchor="false" data-turn="assistant"> What We're Looking For Lightning AI is seeking an experienced Infrastructure Operations Engineer to join our APAC InfraOps function to help scale and operate our next-generation AI infrastructure platform. Our InfraOps team sits at the center of reliability, automation, and operational scale for GPU infrastructure. This team owns break/fix operations, incident response, customer provisioning, observability, and the automation systems that keep complex infrastructure running efficiently. In this role, you’ll work hands-on with large-scale GPU environments, Linux systems, bare metal infrastructure, provisioning workflows, and platform reliability. You’ll partner closely with Infrastructure Engineering, Network Operations, and Software Platform teams to troubleshoot issues, improve operational efficiency, and build automation that reduces manual toil over time. This role is remote and open to candidates residing in Singapore. The role follows a Monday-Friday schedule from 8:00 AM to 5:00 PM local time (UTC+8), with regular participation in an on-call rotation. What You'll Do - At the direction of the Manager of Infrastructure Operations, design, build, and roll out new platforms and patterns to minimize incidents and enable customer facing and internal features. - Deploy updates and improvements to support both Voltage Park’s internal and end customer use cases. - Collaborate with colleagues in Infrastructure Engineering, Network Operations, Customer Success and Software and Platform Development Teams. - Participate in the on-call rotation which is evenly distributed across all team members in a primary / secondary pattern where you are primary then move to a secondary position. What You Will Need Required Qualifications - 8+ years working with Linux as a server / hosting platform, extra points for Ubuntu experience. - 5+ years experience with AWS. - 2+ years experience with Kubernetes and strong container fundamentals. - 2+ years experience with Terraform and Ansible - 2+ years with network attached storage management (via NFS, ceph, or other protocols). Extra points for experience with VAST storage systems. - Experience with monitoring systems (Prometheus, ELK stack). - Familiarity with the gitops workflow. - Software development experience using Python, Go, bash, or other languages for the purposes of automation & connecting systems & APIs together. - Deep networking fundamentals, extra points for experience with datacenter level networks, 400Gb ethernet, and Infiniband. - Experience building and delivering complex systems. - Effective at navigating tradeoffs between design, risk, cost, and outcomes. - Comfortable with navigating ambiguity. - Strong written and oral communication. Nice-to-Haves - Experience with bare metal hardware troubleshooting and provisioning, extra points for working with Dell hardware. - Experience with GPU servers, both in bare metal form or under virtualization. - Deep experience with network switches, routers, and firewalls, particularly SONiC switches, Palo Alto firewalls and Juniper Networks as vendors. - Experience with VAST storage systems Compensation We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $165,000 - $205,000 SGD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Infrastructure Operations Engineer
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. *]:pointer-events-auto [content-visibility:auto] supports-[content-visibility:auto]:[contain-intrinsic-size:auto_100lvh] R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="request-WEB:6da214d3-9e35-4d43-89b6-34d5a76ffba7-1" data-turn-id-container="request-WEB:6da214d3-9e35-4d43-89b6-34d5a76ffba7-1" data-testid="conversation-turn-4" data-scroll-anchor="false" data-turn="assistant"> What We're Looking For Lightning AI is seeking an experienced Infrastructure Operations Engineers to help scale and operate our next-generation AI infrastructure platform. Our InfraOps team sits at the center of reliability, automation, and operational scale for GPU infrastructure. This team owns break/fix operations, incident response, customer provisioning, observability, and the automation systems that keep complex infrastructure running efficiently. In this role, you’ll work hands-on with large-scale GPU environments, Linux systems, bare metal infrastructure, provisioning workflows, and platform reliability. You’ll partner closely with Infrastructure Engineering, Network Operations, and Software Platform teams to troubleshoot issues, improve operational efficiency, and build automation that reduces manual toil over time. This role may be fully remote within the U.S., or hybrid out of one of our office hubs (NYC, SF, Seattle, or London), with occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time. What You'll Do - At the direction of the Manager of Infrastructure Operations, design, build, and roll out new platforms and patterns to minimize incidents and enable customer facing and internal features. - Deploy updates and improvements to support both Voltage Park’s internal and end customer use cases. - Collaborate with colleagues in Infrastructure Engineering, Network Operations, Customer Success and Software and Platform Development Teams. - Participate in the on-call rotation which is evenly distributed across all team members in a primary / secondary pattern where you are primary then move to a secondary position. What You Will Need Required Qualifications - 8+ years working with Linux as a server / hosting platform, extra points for Ubuntu experience. - 5+ years experience with AWS. - 2+ years experience with Kubernetes and strong container fundamentals. - 2+ years experience with Terraform and Ansible - 2+ years with network attached storage management (via NFS, ceph, or other protocols). Extra points for experience with VAST storage systems. - Experience with monitoring systems (Prometheus, ELK stack). - Familiarity with the gitops workflow. - Software development experience using Python, Go, bash, or other languages for the purposes of automation & connecting systems & APIs together. - Deep networking fundamentals, extra points for experience with datacenter level networks, 400Gb ethernet, and Infiniband. - Experience building and delivering complex systems. - Effective at navigating tradeoffs between design, risk, cost, and outcomes. - Comfortable with navigating ambiguity. - Strong written and oral communication. Nice-to-Haves - Experience with bare metal hardware troubleshooting and provisioning, extra points for working with Dell hardware. - Experience with GPU servers, both in bare metal form or under virtualization. - Deep experience with network switches, routers, and firewalls, particularly SONiC switches, Palo Alto firewalls and Juniper Networks as vendors. - Experience with VAST storage systems Compensation We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $160,000 - $200,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Research Engineer / Scientist, Memory
SOLVING SELF-IMPROVING SUPERINTELLIGENCE The human brain is a sponge. Today’s AI brains are brittle and rigid. At Letta, we’re building self-improving artificial intelligence: creating agents that continually learn from experience and adapt over time. Founded by the creators of MemGPT from UC Berkeley’s Sky Computing Lab (the birthplace of Spark and Ray). Backed by Jeff Dean, Clem Delangue, and pioneers across AI infrastructure. Our agents already power production systems at companies like 11x https://www.letta.com/case-studies/11x and Bilt Rewards https://www.letta.com/case-studies/bilt, learning and improving every day. We’re assembling a world-class team of researchers and engineers to solve AI’s hardest problem: making machines that can reason, remember, and learn the way humans do. Note that this role is in-person (no hybrid), 5 days a week in downtown San Francisco. YOUR ROLE You will design the long-term memory architecture for LLMs. At Letta, you'll work with a world-class, tight-knit team of AI researchers and engineers towards our vision of self-improving superintelligence. Advance the field through open publishing of research through papers, technical reports, blog posts, and open-source code. WHAT YOU’RE RESPONSIBLE FOR: - Defining the key abstractions of the LLM memory layer - Building memory architectures that support multiple memory types including temporal sequences, episodic experiences, semantic knowledge, and procedural skills - Researching memory sharing between multiple agents that enable effective multi-agent collaboration - Improving context management techniques that solve the long-context / context derailment problem - Running evaluations for measuring and improving memory for agents WHAT WE'RE LOOKING FOR: - Deep expertise in LLMs and retrieval - Track record of impactful research (breakthrough publications and/or open source contributions) - Ability to balance execution speed with empirical rigor - Real-world impact beyond pure academic work OUR CULTURE SIGNS IT COULD BE A GREAT FIT: - You want to maximize your impact: you want work on a small, incredibly talented team where every individual plays a huge role in the team's success. You wonder what it would have been like to be at OpenAI when it was just a dozen people, or Google when it was just a couple of grad students in a garage. - You’re excited to go head-to-head with tech giants, frontier labs, and other startups that are many times our size in both headcount and funding. - You are fundamentally opposed to closed frontier AI that is controlled by a handful of billionaires and private tech companies. SIGNS IT’S A BAD FIT: - You like stability, and get stressed out when there’s nobody telling you exactly what to do. We look for people that thrive in ambiguity and can intuit the most important problems by talking to customers and dogfooding our product. - You want to work a 9-5, and value clear separation of work from life. The stakes are the highest they've ever been, and the only moat is execution velocity. Operating on a strict 9-5 guarantees failure. - You value titles or want to people-manage. Letta is a flat company where every researcher and engineer is an individual contributor. OUR INTERVIEW PROCESS: - Initial screen (30 min) - Technical screen (1-1.5 hours) - Paid in-person work trial (2 days onsite in SF)
Senior Data Scientist - Product
ABOUT US Legora is redefining how legal work gets done. Not built for lawyers, built with them. We work alongside the world’s best legal teams, who expect excellence, precision, and speed, and we hold ourselves to the same bar. Our AI-native workspace lets legal professionals move faster, think more clearly, and operate with sharper precision. By analysing thousands of documents in minutes and powering end-to-end workflows, we cut through complexity, teams can focus on what matters: judgment, strategy, and outcomes. 2,100+ customers across 80+ countries trust us, including Cleary Gottlieb, Goodwin, Linklaters, White & Case, Dentons, and Barclays. We’ve scaled to $200M+ in ARR, with teams across Europe, North America and APAC, and continue to expand through acquisitions including Qura, Walter AI, Graceview, Cadastral, and Wexler. We partner with world-class performers: including Aaron Judge and the New York Yankees, Ludvig Åberg (and his caddie), and campaigns featuring Jude Law. Joining Legora means three things. - We lean in: ownership over titles, outcomes over intentions. - We fight for excellence: high standards, direct, ego-free feedback. - We grow together: as a team and with our customers. Mission before ego. Everyone contributes. No one coasts. If you’re driven by impact, pace, and raising the bar. This is the place. The role As a Senior Data Scientist for Product at Legora you will turn data into decisions. You'll sit close to the business, taking questions end-to-end: shaping the metric, modelling the data in dbt, running the analysis, and making the recommendation. You'll pull in new data sources when you need to. Insights are useful; impact is what we hire for. We're an AI-first data team. We believe the data function should be redesigned around what AI now makes possible, not retrofitted with it, and we want someone excited to help define what that looks like in practice. There's no single profile we hire for. Some of us are strongest at data modelling and analytics engineering, some at experimentation and causal inference, some at machine learning, some at stakeholder influence. You'll likely be excellent at one or two of these and competent across the rest. That's the bar. We're a small, centralised team supporting the whole company, hiring for the person, not the seat. Depending on your strengths and where we have the biggest gap when you join, you could be embedded primarily with: - Product: instrumentation, feature adoption, user behaviour, A/B testing, shaping the roadmap with PMs and designers. - Finance & RevOps: ARR, NRR, forecasting, board reporting, pricing analytics across a 40-country footprint, and unit economics for an AI-native product. - Growth & Marketing: acquisition funnels, attribution, campaign measurement, lifecycle analytics, and what actually moves enterprise legal buyers. - GTM & Customer Success: pipeline analytics, customer health, expansion signals, and retention drivers in a category that didn't exist three years ago. You'll partner directly with leaders across Product, Engineering, Finance, and GTM, most of whom are unusually data-fluent and will happily open a SQL editor with you. Your work will directly influence how we prioritise, how we sell, how we price, and how we build. What you will be doing - Partner with stakeholders across Product, Finance, GTM, Growth, and beyond to translate ambiguous questions into structured analyses and clear recommendations. - Define the metrics that matter, design the experiments or analyses that test them, and measure the impact of what we ship. - Conduct deep-dive analyses on the questions that move the business, and proactively surface the questions nobody is asking yet. - Model the data you need for your work in dbt, pulling in new sources when necessary, and partner closely with data engineering on anything that needs to scale beyond your immediate use case. - Build dashboards and reporting that scale beyond you, so the company can answer its own questions where possible. - Help shape how the data team operates as we scale: standards, tooling, ways of working. What you'll need - Strong proficiency in SQL and Python. - Solid grasp of data modelling and what it takes to build analytical work that is reliable and trusted. - Excellent communication skills and the confidence to influence decisions through data storytelling, including pushing back when the data doesn't support what someone wants to do. - Genuine depth in at least one of the following, with competence across the rest and curiosity to grow: - Data modelling and analytics engineering (dbt, dimensional modelling, semantic layers, self-service) - Experimentation and causal inference (A/B test design, quasi-experiments, statistical rigour) - Machine learning and applied data science (forecasting, prediction, segmentation, evaluation) - Product analytics and metric design (funnels, cohorts, adoption frameworks, North Star metrics) Nice to have - Experience in a product-led or SaaS environment, ideally B2B. - Hands-on experience with our stack: Snowflake, dbt, Hex, Dagster. - Prior experience as an early data hire at a fast-growing company, i.e. you've built the muscle, not inherited it. Most importantly, you are someone who - "Gets stuff done" and understands building a $10bn company isn't always glamorous and takes hard work and long hours. - Thrives in a fast-paced environment where the answers aren't always clear and processes are few. - Is genuinely domain-curious. You don't need to have worked on every part of a business, but you should be excited to. Legora is an Equal Opportunity Employer At Legora, we believe great teams are built on diversity of thought and experience. We’re proud to be an equal opportunity employer and committed to creating an inclusive, high-performance culture where everyone can do their best work. We welcome people of all backgrounds and don’t discriminate based on race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.
AI Engineer
ABOUT US Legora is redefining how legal work gets done. Not built for lawyers, built with them. We work alongside the world’s best legal teams, who expect excellence, precision, and speed, and we hold ourselves to the same bar. Our AI-native workspace lets legal professionals move faster, think more clearly, and operate with sharper precision. By analysing thousands of documents in minutes and powering end-to-end workflows, we cut through complexity, teams can focus on what matters: judgment, strategy, and outcomes. 2,100+ customers across 80+ countries trust us, including Cleary Gottlieb, Goodwin, Linklaters, White & Case, Dentons, and Barclays. We’ve scaled to $200M+ in ARR, with teams across Europe, North America and APAC, and continue to expand through acquisitions including Qura, Walter AI, Graceview, Cadastral, and Wexler. We partner with world-class performers: including Aaron Judge and the New York Yankees, Ludvig Åberg (and his caddie), and campaigns featuring Jude Law. Joining Legora means three things. - We lean in: ownership over titles, outcomes over intentions. - We fight for excellence: high standards, direct, ego-free feedback. - We grow together: as a team and with our customers. Mission before ego. Everyone contributes. No one coasts. If you’re driven by impact, pace, and raising the bar. This is the place. THE TEAM AI Enablement makes Legora AI-native by default. We work across three streams in parallel: building internal agents and tools, equipping teams to build their own, and owning the standards, access and guardrails that let everyone move fast safely. We own the AI platforms and the internal products built on them. So far that includes Leya, an internal knowledge agent live in Slack that answers questions about Legora with cited sources and automates parts of our RFP and security questionnaire work. A structured, agent-readable knowledge base assembled from knowledge each domain continues to own, where agents propose changes and humans approve them. Leyf, a platform for internally built apps that lands anyone's app on shared infrastructure with guardrails scaled to how much damage it could do. And a Skills Hub, so that something one person works out becomes something the whole company can use rather than staying on their laptop. The team is small and the mandate is large. That is the job. WHAT MAKES THIS HARD Legora is an AI company of around a thousand people, most already fluent and on current tools. Internal AI here is not an adoption problem. Nobody needs convincing, which means there is nowhere to hide behind change management or training. If something we build is not used, it is because it was not good enough. Our colleagues know what good looks like and will not use something worse than what they think they could build themselves in an afternoon. So we ship things people genuinely want, and the foundations arrive with them. That constraint does not go away. The mandate is also larger than the team. The part no individual can do for themselves is the infrastructure, the access model and the architecture underneath, and getting that right across a company this size is the actual work. It does not come with a specification. WHAT YOU WILL DO You will take broad ownership of how AI works inside Legora and of the platforms we build to make it work. - Build internal agents, tools and platforms, and treat them as products rather than projects. Quality, reliability and whether they actually serve the business are yours, not someone else's - Take a broad goal, work out what is actually required, and break it into the work yourself - Own what you build end to end, from the architecture through to whether people use it and it holds up in production - Shape what we should build and in what order, and argue for it - Design the foundations: knowledge architecture, access and permissions, evaluation and monitoring, the guardrails that scale with risk - Work directly with the people who will use what you build, across the whole company, including the parts furthest from engineering WHO WE ARE LOOKING FOR - Strong engineering fundamentals. You build production systems, not prototypes that need someone else to finish them - Real depth with LLM-based systems. Agents, retrieval, evaluation, tool use. You know where these systems break and you design for it - Ownership by instinct. You do not wait for a specification. When the requirement is unclear or wrong, you say so and propose something better - Three kinds of understanding at once. Technical, domain and business. You can hold a conversation about architecture and a conversation about what the business actually needs, and connect them - Openness. You take feedback, build on other people's ideas, change your mind when the evidence moves, and push for the strongest outcome rather than the one you proposed first - Comfort with ambiguity. New team, fast growth, decisions that get revisited as we learn. That should sound appealing rather than annoying - TypeScript. It's what we work in, and where our shared patterns live - No aversion to infrastructure. We own ours, so Terraform and cloud providers are part of the work rather than someone else's problem - You work with code agents daily. Not as an experiment, as how you build Legora is an Equal Opportunity Employer At Legora, we believe great teams are built on diversity of thought and experience. We’re proud to be an equal opportunity employer and committed to creating an inclusive, high-performance culture where everyone can do their best work. We welcome people of all backgrounds and don’t discriminate based on race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.
Member of Technical Staff
THE OPPORTUNITY We are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays. WHO YOU ARE - You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling. - You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators. - You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale. - You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics. - You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently. WHAT SETS YOU APART - You have experience in computational biology or protein design. You have worked on ML-driven projects in biology. - You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields. YOUR RESPONSIBILITIES - Build machine learning models that work in the physical world [~90% of your time]: - Contribute to a careful curation of our training and evaluation data. - Propose and build ML evaluation metrics that align with real world success and company goals. - Quickly prototype generative models against our lead metrics and perform deep analyses of improvements. - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards. - Contribute to the maintenance of our compute and ML development infrastructure. - In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab. - Quickly learn from wet lab results and feedback data to our models. - Self development [~10% of your time]: - Stay on top of the latest developments in ML. - Gain a strong working understanding of protein and cell biology. - Participate in knowledge sharing, e.g. organize and present at our internal reading group. - Attend and present at conferences. APPLY We offer strongly competitive compensation and benefits packages, including: - Private health insurance - Pension/401(K) contributions - Generous leave policies (including gender neutral parental leave) - Hybrid working - Travel opportunities and more We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models. We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
Computational Protein Designer
Computational Protein Designer THE OPPORTUNITY We are seeking a Computational Protein Design Scientist to join our team working at the interface of generative AI and synthetic biology. Working closely with our Lead Computational Protein Designer, you will play a key role amongst a team of scientists designing and engineering proteins for specific functions. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. Using your blend of computational expertise and in-depth biochemical understanding of proteins, you will generate insights to improve protein functionality and operate at the interface between our machine learning and experimental platform units, working closely to seamlessly integrate AI generations and lab validation data. WHO WE ARE At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology. Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites. We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission. WHO YOU ARE - You are a computational protein designer. You have a proven track record of running protein design campaigns end-to-end, successfully leveraging novel computational tools and knowledge of biochemistry or structural biology to design proteins to functional requirements and applications in synthetic biology. - You are a generative modelling enthusiast You have AI generative modeling experience, including model training and large scale inference. - You are a successful scientist. You have a PhD (or equivalent industry experience) in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bio/chem engineering, or a related field. Your research experience was in protein biochemistry using computational expertise. - You collaborate with experimentalists. You have experience collaborating with experimental (i.e. wet lab) teams to achieve protein design objectives. - You are an owner. You have a proven track record of delivering successful commercial and / or academic research projects, demonstrated through publications, patents, and/or commercially impactful outcomes, as well as other contributions to the scientific community. - You are a connector. You love to connect people and enable them to perform at their highest levels. You have excellent communication and presentation skills with the ability to convey complex scientific concepts to both technical and non-technical audiences. - You are a mission driven innovator. You are passionate about making a positive impact on the world, whether it's for patients, partners or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. - You thrive in a dynamic and ambiguous environment. You excel in a fast-paced setting where goals must be achieved efficiently and urgently. You have a keen eye for creating, then optimizing processes to improve speed and repeatability. You are an advocate for lab automation, both through hardware and software WHAT SETS YOU APART (PREFERRED BUT NOT REQUIRED) - You have experience with generative AI. You have experience leveraging generative AI (or other machine learning models) in synthetic biology applications. - You have experience with homology-based and structural bioinformatics, and are able to answer scientific questions using very large databases. - You have helped scale a young biotech before. You have worked in startups and helped the company grow. YOUR RESPONSIBILITIES - Leverage our proprietary generative AI models to design proteins for experimental validation: - Analyze protein design problems based on functional requirements, biochemistry, structural biology and sequence homology - Generate designs using our proprietary generative AI models and optimize designs for experimental validation - Coordinate with our lab-based protein engineers to plan and optimize the design process and validation strategy - Leverage our proprietary data to improve our models: - Analyze and leverage our experimental results to improve the next round of designs and increase our success rate over validation rounds - Collaborate with machine learning scientists to fine-tune and prompt our models - Collaboration and communication: - Be an effective interface between machine learning model development and experimental validation - Capture bioengineering learnings and feedback to our machine learning unit, and vice versa - Foster a collaborative and innovative environment, proactively finding opportunities to innovate and create clarity and alignment between different units - Contribute to our computational tools: - Help improve the way we use, serve and integrate our AI models, by feeding back to the software engineers and foundational machine learning unit - Help improve our data management systems and workflows - Scientific excellence and self development: - Work to the highest scientific standards (publication-grade work) Stay on top of relevant developments in synthetic biology - Continue building your understanding of generative AI as well as expanded areas of protein and cell biology - Participate in knowledge sharing, e.g. organize and present at our internal reading group. - Attend and present at conferences when relevant APPLY We offer strongly competitive compensation and benefits packages, including: - Private health insurance - Pension/401(K) contributions - Generous leave policies (including gender neutral parental leave) - Hybrid working - Travel opportunities and more We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models. We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
Senior Software Engineer - Managed Kubernetes
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. ABOUT THE ROLE We are seeking a Senior Software Engineer to join our Managed Kubernetes (Mk8s) team. You will play a crucial role in shaping the architecture, reliability, and automation of our Kubernetes-based infrastructure, which powers mission-critical workloads across our global platform. Lambda is building the AI Cloud of the future. We are seeking a Senior Software Engineer to help our development of our Managed Kubernetes platform. Think GKE, but purpose-built for AI workloads and running on bare metal. In this role, you will help build the infrastructure that powers the next generation of AI training and inference at scale. As a Senior Engineer on our Orchestration team, you will contribute to Lambda's managed orchestration services, including Managed Kubernetes, Managed Slurm on Kubernetes, and higher-level platform services for inference and AIOps. You'll work at the intersection of distributed systems, GPU-accelerated computing, and Cloud Native infrastructure to build systems that are reliable, performant, and elegantly simple for our customers. This is not a role for someone who just operates Kubernetes; it's a role for an engineer who understands how compute, network, storage, and security interact, and can build solutions that account for that context — even while focused primarily on the orchestration layer. You'll be working closely with NVIDIA's open-source ecosystem, and partnering with internal teams across the stack to deliver a world-class managed platform. WHAT YOU’LL DO - Design, build, and maintain scalable control plane services, operators, and custom Kubernetes controllers; develop automation in Go/Python for end-to-end cluster lifecycle management — provisioning, upgrades, patching, and deletion - Build GPU-aware orchestration systems, working within the platform architecture to support GPU scheduling and resource allocation - Partner with the Network team on networking solutions for AI workloads: CNI integration (Cilium, Multus), high-performance fabrics (InfiniBand, RoCE), RDMA, and GPUDirect - Write resilient systems that handle failure gracefully — timeouts, retries, backoff, and degraded-mode operation — across large-scale distributed environments - Develop platform services for inference: model serving infrastructure, autoscaling based on inference load, and multi-model deployment patterns - Build internal tools and CLIs that let ML/AI teams deploy and monitor their own inference services - Support and debug production issues through on-call rotation REQUIRED QUALIFICATIONS - Have 6+ years of experience in software engineering, with a track record of owning significant technical scope within a team (e.g., driving a project from design through production, or acting as a de facto tech lead on a workstream) - Deep understanding of Kubernetes internals: controllers, schedulers, operators, CRDs, CSI, CNI, and the extension patterns that make Kubernetes powerful - Solid grasp of distributed systems fundamentals — fault tolerance, graceful degradation, and failure handling in large-scale environments - Experience operating the control plane and low-level pieces of large-scale Kubernetes clusters - Experience with observability at scale: Prometheus, Grafana, distributed tracing, and building actionable alerting systems - Strong programming skills in Go and Python; ability to collaborate effectively on shared codebases - Solid knowledge of Linux systems, networking, containers, and cloud infrastructure - Take pride in owning and delivering core components of products and platforms PREFERRED QUALIFICATIONS - Experience building and operating managed Kubernetes services (GKE, EKS, AKS, or similar) or working on Kubernetes control plane components - Hands-on experience with NVIDIA's GPU/networking ecosystem: GPU Operator, device plugins, DCGM, MIG, Network Operator, NCCL tuning, or similar - Familiarity with HPC and traditional job schedulers (Slurm) and Kubernetes-native batch scheduling (KAI, Volcano, Kueue) - Familiarity with GPU, InfiniBand, RDMA, or high-performance computing on Kubernetes - Exposure to storage architecture for AI/ML workloads - Past contributions to CNCF projects or Kubernetes SIGs a plus If you don’t meet all of these requirements but believe you may be a good fit, please still apply and provide a cover letter that helps us understand your experience and readiness for this role. WHY LAMBDA Lambda is building the essential infrastructure for the AI era. We're not just another cloud provider: we're a company founded by ML practitioners, for ML practitioners. Our customers include leading AI research labs and enterprises pushing the boundaries of what's possible with artificial intelligence. What makes this role special: - You'll be building core platform services the world's largest AI companies will consume - NVIDIA partnership: Deep integration with NVIDIA's GPU and networking stack, working with cutting-edge open-source tooling - Real technical challenges: Massive scale GPU clusters and the unique demands of AI workloads - Cross-stack exposure: Work at the intersection of Kubernetes, networking, storage, and compute — gaining depth across the full infrastructure stack that powers AI workloads, not just the orchestration layer - Direct impact: Your work enables AI breakthroughs. Every model trained on Lambda benefits from systems you build - World-class team: Work alongside engineers with deep expertise in ML, systems, and infrastructure Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG - Our values are publicly available: https://lambda.ai/careers - We offer generous cash & equity compensation - Health, dental, and vision coverage for you and your dependents - Wellness and commuter stipends for select roles - 401k Plan with 2% company match (USA employees) - Flexible paid time off plan that we all actually use Equal Opportunity Employer Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Head of Content
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco or San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. Every GPU cloud provider claims to offer faster, cheaper, and more reliable solutions. ML engineers and decision-makers must sift through these promises to form a trustworthy opinion. Lambda fills the gap between claims and real outcomes. You own the entire process, from strategy to production. Your audience may be a researcher testing a training run or an enterprise buyer building a procurement case, but you control the message. You set the standards, build the system, and define the quality. What You’ll Do - Own the strategy and the roadmap. Map content to the full buyer journey, from awareness and education through evaluation and retention, against Lambda's growth, product, and brand goals. - Set and maintain the quality bar. Establish rigorous quality standards that empower the team to execute with excellence independently. - Run the production system. Intake, prioritization, drafting, review, and launch, at the cadence of product and model releases. - Shape how AI gets used in content production. Build the workflows and standards that let AI speed up the work without lowering the bar. - Own discovery. SEO and generative engine optimization (GEO) are how most people find us. Keyword research, content gap analysis, and on-page work are inputs to strategy, not a cleanup pass at the end. - Build the executive voice. Turn Lambda's narrative into thought leadership that holds up in front of ML engineers and data center operators. - Partner on launches. Work with technical product marketing and growth so every major launch and campaign is supported by a well-timed, end-to-end content program. - Own measurement. Traffic, engagement, pipeline influence, and content-assisted conversion, fed back into what the team makes next. - Build the team. Hire, develop, and shape the content org as it grows. You - You have taste. You can't walk past a vague sentence or a case study that says nothing. You know the difference between content that's technically correct and content that's actually worth reading, and you can teach that difference to someone else. - You're deeply curious about AI. You follow model releases, read top papers, and understand why memory bandwidth matters to an ML engineer. You can tell when a technical claim is load-bearing and when it's decoration. - You have a point of view on AI-assisted content. You've produced work with these tools yourself, you know what to trust them with, and you have opinions about where they break down. - You've led a content function, not just a content calendar. You've managed and grown people, and you can point to content you shipped and results you can attribute to it. - You think in systems. You design content architectures, not individual pieces. You understand how a benchmark post, a technical guide, and a case study work together. - You balance strategy and execution. You can build a 12-month roadmap and then sit with a writer to get one hard piece over the line. Neither mode intimidates you. - You excel at cross-functional leadership. You work with technical product marketers, researchers, engineers, designers, and web marketers, and you synthesize all of it into one coherent editorial vision. - You're rigorous about measurement. You define what working means, instrument for it, and act on what you find. Nice to Have - Experience writing or editing for ML practitioners, whether at an infrastructure company, a research lab, or a developer tools start-up. - Experience building AI-assisted production workflows for content or other creative work. - A track record building organic and generative search visibility in the AI space. Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG - Our values are publicly available: https://lambda.ai/careers - We offer generous cash & equity compensation - Health, dental, and vision coverage for you and your dependents - Wellness and commuter stipends for select roles - 401k Plan with 2% company match (USA employees) - Flexible paid time off plan that we all actually use Equal Opportunity Employer Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Forward Deployed Engineering Manager
Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: - Enterprise Platform & Tools : Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale - Frontier Data Labeling Service : Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models - Expert Marketplace : Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us - High-Impact Environment : We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. - Technical Excellence : Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. - Innovation at Speed : We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. - Continuous Growth : Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. - Clear Ownership : You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. The role The FDE Manager leads and grows the team of Forward Deployed Engineers who own the high-level technical side of our customer data programs. FDEs scope tasks, design the pipelines and measurement that turn a customer's goal into a training signal, write the instructions that guide Alignerrs, and work out what each customer actually needs from their data. The FDE Manager owns the people who do that work — their craft, their growth, and how they're deployed across domains and customers — and is accountable for the technical quality and consistency of what the team produces. This role sits at the intersection of people leadership, technical depth, and delivery quality. The FDE Manager must understand the technical substance of our projects well enough to coach on scoping and pipeline design, pressure-test instructions, judge whether a project's data will genuinely move the customer's model, and raise the bar on measuring quality early rather than late. It's a player-coach role: you lead people, but you stay close enough to the work to set and defend the craft bar yourself. The FDE Manager reports to the Services lead and partners closely with the SPL Manager, Deployment Leads, and General Managers. A core part of the role is keeping FDEs at the right altitude — focused on higher-level technical and customer-facing work — and actively handing the day-to-day running of projects to the SPLs and Pod Leads, so the team's most expensive technical talent is never absorbed into project operations. The FDE Manager also owns FDE onboarding and is the steward of the FDE career path, which runs from FDE to FDE 2 to FDE Manager, with branches toward the Forward Deployed Researcher (FDR) track and, in time, toward General Manager. What You'll Do - Lead the FDE team end-to-end: hire, coach, manage performance, and develop careers across the FDE track and toward FDR or GM. - Own the supply side of FDE staffing: commit FDEs to the staffing cadence and match them to projects by skill and development need, balancing each FDE's preferred vertical with where the work is, and staffing to the phase of a project rather than parking people for its full length. - Set and uphold the craft bar: sharp task scoping, sound pipeline and measurement design (including the LLM-as-judge and quality instrumentation that surface problems early), clear instruction writing, and compelling customer-facing presentation of findings. - Protect FDE focus: keep day-to-day project operations with the SPLs and Pod Leads, and keep FDEs on scoping, technical depth, and what the customer needs from the data. - Own FDE onboarding and the bar that certifies a new FDE as ready to be staffed: define which projects are eligible to onboard on, maintain the instruction and Loom repository, and run the onboarding program — including the core exercise (read a past project's instructions, explain them back, and write a new version in the repo). - Drive reuse and leverage: build the templates, tooling, and playbooks that stop FDEs rebuilding pipelines and instructions from scratch each project, so the team's capacity compounds as we scale. - Ensure FDEs work hand-in-glove with FDRs on research, efficacy, and customer needs, and partner with whoever owns quality sign-off so quality is caught in flight, not at delivery. - Partner with the SPL Manager, Deployment Leads, and GMs on staffing, delivery, and alignment with customer objectives. - Step in on escalations when a pipeline, delivery, or customer relationship is at risk. - Maintain a clear, live view of team capacity, utilization, and bench across active projects. What You'll Own - The capability and craft bar of the FDE team. - How quickly and consistently new FDEs reach a staffable standard. - Healthy deployment — the right FDEs on the right projects, at the right altitude and utilization. - A growing bench of FDEs developing toward FDR and future leadership. What We're Looking For - A strong forward-deployed / FDE background, or significant experience managing technical or delivery people — and readiness to be a hands-on, player-coach manager. - Strong technical fluency in our domain: enough depth in frontier-data work, RL environments, data pipelines, and quality/evaluation to coach credibly on scoping, pipelines, judge design, and data quality. - Excellent judgment on what makes data genuinely useful to a customer — how to translate ambiguous requirements into clear plans, and how to tell whether data will actually move a model. - A track record of developing people and giving direct, useful feedback. - A high bar for quality paired with the ability to deliver against ambitious timelines. - Comfort operating in ambiguous, fast-scaling environments where the processes are still being built. - The ability to manage multiple people and projects at once without losing attention to detail. Nice to Have - Direct experience with RLHF, reinforcement-learning environments, evaluation/benchmark work, or LLM-as-judge systems. - Experience working with forward-deployed engineers, solutions engineers, or implementation teams. - Experience building onboarding programs, instruction systems, or training content. - Experience scaling a team and its operating processes in a high-growth environment. What Success Looks Like In your first several months, you'll take ownership of the FDE team, raise the bar on scoping, pipeline, and instruction quality, and get onboarding running smoothly — eligible projects defined, the instruction and Loom repository in good shape, and new FDEs reaching a staffable standard faster and more consistently. You'll build strong working relationships with the SPL Manager, Deployment Leads, and GMs, keep FDEs well-deployed and at the right altitude, and become the person the team relies on for craft and career growth. Over time, you'll define how FDEs work at scale: the templates, tooling, and playbooks that let the team produce more without rebuilding from scratch, a measurement-and-quality craft bar that surfaces problems early, and a pipeline of FDEs growing into FDRs and future leaders. Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location. Annual base salary range $190,000 - $250,000 USD Life at Labelbox - Environment : Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making - Growth : Career advancement opportunities directly tied to your impact - Vision : Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy : Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice . Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.
Engineer, Supercomputing & Distributed Systems
ABOUT KREA At Krea, we are building next-generation AI creative tools. We're dedicated to making AI intuitive and controllable for creatives - our mission is to build tools that empower human creativity, not replace it. We believe AI is a new medium that allows us to express ourselves through various formats - text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. We recently took this a step forward with the launch of Krea 2 https://www.krea.ai/blog/krea-2-image-model, our first foundation model, built completely from scratch for aesthetic diversity and stylistic control. We've raised over $83M and are backed by world-class investors such as a16z, Bain Capital, and Abstract. We work full-time and in-person at our waterfront office in San Francisco. We care about creativity: our team includes musicians, designers, visual artists, and engineers. SUPERCOMPUTING / AI INFRA AT KREA We build and operate the infrastructure for Krea's research and inference. Distributed training, 1000+ K8s GPU clusters, petabyte scale data pipelines, etc. We build a lot of this from scratch — custom distributed datastores, job orchestration systems, and streaming pipelines that replace tools like Kafka and Ray for modern AI workloads at scale. EXAMPLE PROJECTS: DISTRIBUTED DATA SYSTEMS - Design multi-stage pipelines that turn petabytes of raw data into clean, annotated datasets - Run classification models on billions of images - Deploy and combine LLMs to caption massive multimedia data GPU INFRASTRUCTURE - Manage distributed training and inference on 1000+ GPU Kubernetes clusters - Solve orchestration and scaling for large-scale GPU job processing - Scale workloads and research between clusters in multiple datacenters DISTRIBUTED TRAINING - Profile and optimize dataloaders streaming thousands of images per second - Profile and debug InfiniBand networking on huge training runs - Build fault tolerance systems for large-scale pretraining - Collaborate with researchers on evolving RL infrastructure APPLIED ML PIPELINES - Find clean scenes in millions of videos using distributed shot-boundary detection - Customize and train models to filter billions of images for questions like "is this a screenshot?" - Build the systems that bridge raw cluster capacity and research output WHO WE'RE LOOKING FOR Systems people. If you've read a blog post about InfiniBand debugging or building a custom distributed database and thought "I want to do that" — this is that team. You'll spend your time working heavily with Python, Kubernetes, Torch, and data tools like DuckDB, Arrow, etc. It's OK if you don't have K8s or ML experience — the main thing we hire for is an intuition for distributed systems, and a great mental model of how systems interact and function under different conditions. STRONG CANDIDATES MAY HAVE EXPERIENCE WITH… - Python, PyArrow, DuckDB, SQL, massive relational databases, PyTorch, Pandas, NumPy… - Kubernetes - Designing and implementing large-scale ETL systems - Fundamental knowledge of containerization, operating systems, file-systems, and networking - Distributed systems design - Distributed training systems (NCCL, InfiniBand, RDMA) - Streaming and event processing systems (Kafka, Pulsar, or similar) - PyTorch internals, custom dataloaders, and training infrastructure WHAT WE OFFER - Team: Work alongside a world-class team building the future of AI creative tooling - Impact: Significant scope and company-wide impact - Competitive compensation: generous salary & equity packages - Health & wellness: 100% health & 99% dental/vision insurance premiums covered for employees, health FSA accounts, & long-term disability coverage - Time off: Flexible PTO policy - Financial planning: 401k with a 4% company-sponsored match - Meals in the office: breakfast, lunch, dinner - you name it, we'll cover it - Transit: Ubers covered to & from the office - Sponsorship: We're open to sponsoring international visas where we can (e.g., STEM OPT, OPT, H-1B, O-1, E-3). - And more! Please note the above benefits & perks are for full-time employees
Staff Software Engineer (Inference Platform), Lond...
Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery. Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you. About Iso Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI. Your Impact We are building the largest foundation models in biotech and applying them immediately to cure disease. You will play a pivotal role in ensuring the reliability and scalability of the foundations that make this possible. As a Principal Engineer, you will lead the efforts to harden our systems, ensuring our groundbreaking AI is built on an unshakeable base, working closely with the research team and the Applied ML teams to ensure the infrastructure is stable, reliable and can operate with more data and larger models as we grow. What You Will Do - Develop and operate our inference platform, serving fleets of cutting-edge machine learning models to scientific applications. - Design strategy and build roadmaps for maturing the platform. - Architect and optimize our next-generation inference services. You will solve core scaling limits, ensuring high-throughput performance and feature parity across our model serving stack. - Contribute to core technical decisions on tooling and architectural design while partnering with science, product, and operations teams to align infrastructure with biotech R&D cycles. - Deliver high-quality and well-tested user-focused features. Skills and Qualifications Essential: - Proven experience in architecting and managing large-scale AI/ML workloads in a production environment. - Orchestration: Significant experience deploying and managing complex workloads within Kubernetes. - Expertise in cloud compute design, specifically within Google Cloud Platform (GCP). - Professional familiarity with NVIDIA GPU generations and the intricacies of high-performance compute. - Strong programming skills and a "reliability-first" approach to software development. Nice to Have: - A career history that spans both ML Software Engineering and Infrastructure SRE roles. - Experience leading multi-disciplinary projects and navigating complex stakeholder requirements in a fast-paced environment. - Familiarity with workload scheduling, ML efficiency research, and hardware benchmarking. - Experience with Google TPU generations and specialized ML-driven R&D cycles. Culture and values We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it. Thoughtful Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day. Brave Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. Determined Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we. Together Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere. Creating an extraordinary company We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. Hybrid working It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call. Please note that when you submit an application, your data will be processed in line with our privacy policy . >> Click to view other open roles at Isomorphic Labs
Staff Software Engineer (Forward Deployed)
About Invisible Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most. Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere. Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets. Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology. About The Role As a Staff Forward Deployed Engineer (FDE) at Invisible, you'll lead high-impact, AI-powered solutions that reshape how our clients operate their most critical workflows. You won't just build and deploy — you'll drive the strategy, architecture, and execution of end-to-end systems, working directly with clients. This is a hybrid role: equal parts AI engineer, software builder, and technical consultant. It's perfect for someone who wants to be hands-on with models and close to the impact they generate. The team is increasingly focused on applied AI work — building and deploying LLM-powered and agentic systems in production — so strong ML engineering instincts can be a valuable addition alongside your architecture and leadership experience. What You’ll Do - Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems - Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems - Lead architecture design and trade-off discussions across performance, scalability, cost, and reliability — including for ML/AI-specific systems like RAG pipelines and production-grade AI applications - Own projects from first discovery call through full deployment — including client-facing delivery, internal coordination, and post-launch iteration - Build shared infrastructure, reusable components, and internal playbooks to level-up the team, including MLOps practices for model versioning, monitoring, and lifecycle management - Coach and mentor mid-level engineers and help shape the culture of forward-deployed AI engineering at Invisible What We Need - 8+ years of software engineering experience, including significant time spent building data, ML, or backend systems - Python & ML/LLM Frameworks: Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems, including LLMs and AI Agents - Deployment & Infrastructure: Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS, Azure) - Platform Orchestration: Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance - Data Management: Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes - ML Operations (for teams with an applied AI/ML focus): Experience with MLOps frameworks and best practices — model versioning, monitoring, and lifecycle management — and designing scalable ML systems such as RAG pipelines - Strong product and system design instincts — you understand business needs and how to translate them into technical architecture - Experience building usable systems from messy data and ambiguous requirements - Excellent communication and client-facing skills; you've led conversations with technical and non-technical stakeholders alike - Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments - Be willing to be on-call for our customers when situations arise - Travel: Willingness to travel for on-site client engagements as needed - Onsite: Available to work from the office a few days per week, depending on team needs — some NYC-based teams require 3 days per week onsite; your specific requirement will depend on the team you're placed with What’s In It For You Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity. The annual salary range for this position, depending on level, is: $210,000 - $300,000 USD You can find more information about our geographic pay tiers here . During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living. *Bonuses and equity are included in all full-time offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process. What It's Like to Work at Invisible: At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI. We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re okay with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in. Country Hiring Guidelines: Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process. AI Interviewing Guidelines: Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates. Accessibility Statement: We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request. Here is the link the google form: https://docs.google.com/forms/d/e/1FAIpQLScqsu0PCQ0m0lwt-VFeXovNbZxWk0jogv8QI_ciGqZsIbSBjQ/viewform?usp=sharing&ouid=102356854798492362557 Equal Opportunity Statement: We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law. Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision-making please contact us.
Principal Backend Engineer (Forward Deployed)
About Invisible Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most. Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere. Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets. Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology. About The Role As a Principal Forward Deployed Engineer (FDE) at Invisible, you'll lead high-impact, AI-powered solutions that reshape how our clients operate their most critical workflows. You won't just build and deploy — you'll drive the strategy, architecture, and execution of end-to-end systems, working directly with clients. This is a hybrid role: equal parts AI engineer, software builder, and technical consultant. It's perfect for someone who wants to be hands-on with models and close to the impact they generate. The team is increasingly focused on applied AI work — building and deploying LLM-powered and agentic systems in production — so strong ML engineering instincts can be a valuable addition alongside your architecture and leadership experience. What You’ll Do - Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems - Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems - Lead architecture design and trade-off discussions across performance, scalability, cost, and reliability — including for ML/AI-specific systems like RAG pipelines and production-grade AI applications - Own projects from first discovery call through full deployment — including client-facing delivery, internal coordination, and post-launch iteration - Build shared infrastructure, reusable components, and internal playbooks to level-up the team, including MLOps practices for model versioning, monitoring, and lifecycle management - Coach and mentor mid-level engineers and help shape the culture of forward-deployed AI engineering at Invisible What We Need - 10+ years of software engineering experience, including significant time spent building data, ML, or backend systems - Python & ML/LLM Frameworks: Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems, including LLMs and AI Agents - Deployment & Infrastructure: Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS, Azure) - Platform Orchestration: Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance - Data Management: Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes - ML Operations (for teams with an applied AI/ML focus): Experience with MLOps frameworks and best practices — model versioning, monitoring, and lifecycle management — and designing scalable ML systems such as RAG pipelines - Strong product and system design instincts — you understand business needs and how to translate them into technical architecture - Experience building usable systems from messy data and ambiguous requirements - Excellent communication and client-facing skills; you've led conversations with technical and non-technical stakeholders alike - Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments - Strong engineering background demonstrated by a Bachelor's degree in Data Science, Computer Science and related fields OR equivalent professional experience - Be willing to be on-call for our customers when situations arise - Travel: Willingness to travel for on-site client engagements as needed - Onsite: Available to work from the office a few days per week, depending on team needs — some NYC-based teams require 3 days per week onsite; your specific requirement will depend on the team you're placed with What’s In It For You Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity. The annual salary range for this position, depending on level, is: $250,000 - $300,000 USD You can find more information about our geographic pay tiers here . During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living. *Bonuses and equity are included in all full-time offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process. What It's Like to Work at Invisible: At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI. We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re okay with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in. Country Hiring Guidelines: Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process. AI Interviewing Guidelines: Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates. Accessibility Statement: We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request. Here is the link the google form: https://docs.google.com/forms/d/e/1FAIpQLScqsu0PCQ0m0lwt-VFeXovNbZxWk0jogv8QI_ciGqZsIbSBjQ/viewform?usp=sharing&ouid=102356854798492362557 Equal Opportunity Statement: We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law. Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision-making please contact us.
Lead Product Manager, AI Hub
Help Build the Future of Healthcare AI Infinitus is AI communications in service of patients. Healthcare is inherently complex and siloed. We’re pioneering agentic communications to connect the entire system — any stakeholder, any channel, inbound and out. The result is intelligent care that reduces patient anxiety, increases speed to treatment, and enables teams to scale impact without stretching resources. Our system combines industry-leading safety guardrails with the largest dynamic knowledge graph built on millions of real-world interactions. It’s why 44% of the healthcare Fortune 50 trusts Infinitus to turn fragmented touchpoints into seamless care for better patient outcomes. The Mission At Infinitus, our mission is simple: create time for healthcare by making access, adherence, and affordability easier than ever. We’ve automated over 7 million calls and 100M+ minutes of conversation — saving millions of hours for patients and providers. Backed by over $100M from top investors including Google Ventures, Kleiner Perkins, Andreessen Horowitz, and Coatue, we’re a team that challenges the status quo and moves fast at the intersection of AI and healthcare. Infinitus was recently named to Fast Company's World's Most Innovative Companies and Business Insider’s top startups in healthcare. The AI Hub is Infinitus’s AI-first platform for patient support—bringing together AI agents, human experts, and enterprise workflows to help patients access, afford, and stay on therapy. It is redefining how specialty pharmaceutical companies engage with patients, replacing fragmented, manual operations with intelligent, scalable, and always-on experiences. In this role, you will own the vision, strategy, and roadmap for the AI Hub. You’ll define how the platform evolves across every stage of the patient journey, balancing cutting-edge AI capabilities with the operational excellence, safety, and human expertise required in healthcare. You’ll work across engineering, AI, operations, clinical, customer success, and commercial teams to deliver measurable outcomes for patients and customers. This is one of the highest-impact product roles at Infinitus. You’ll shape the future of AI-powered patient support, define the operating model that combines AI and humans at enterprise scale, and help establish Infinitus as the trusted platform powering the next generation of healthcare communications. WHAT YOU'LL OWN - Product strategy and roadmap for the AI Hub across the entire patient journey — benefit verification, prior authorization follow-up, enrollment, financial assistance, and adherence — as one connected experience, not a set of disconnected tasks. - The AI-and-human operating model: defining what agents handle autonomously, what routes to human experts, and how the handoff carries full context so patients never repeat themselves. - Automation strategy: continuously expanding what AI can safely handle without degrading accuracy, and instrumenting the system so you know exactly where and why humans are still needed. - The commercial and customer story: partnering with sales, customers, and leadership to translate what pharma manufacturers and specialty pharmacies need into a product that wins and scales program by program. - Cross-functional leadership across engineering, AI/ML, operations, implementation, clinical, and compliance — and mentorship that raises the standard for other PMs on the team. MUST-HAVES - 5+ years in product management, including ownership of a product line or portfolio and a track record of setting strategy, not just executing a roadmap. - Deep specialty pharma / patient support domain expertise - you understand hub services, patient support programs (PSPs), benefit verification, prior authorization, copay and financial assistance, and payor/PBM workflows from the inside, and you know where patients drop off and why. - Strong systems thinking - comfortable designing workflows where software and human operations are both first-class parts of the product. - Fluency with data: you define the metrics, own the dashboards, and make roadmap calls from evidence. - Proven ability to operate in a regulated, safety-first environment where accuracy and compliance are non-negotiable. - Senior cross-functional and executive-facing leadership, including direct work with customers. BONUS - Consulting experience serving pharma / life sciences clients. - Working knowledge of CRMs (e.g., Salesforce Health Cloud / Life Sciences Cloud) and how they anchor hub and PSP workflows. - Experience owning implementations — the messy, program-by-program work of getting a solution live with a customer. - Experience shipping AI/ML or agentic products Why You’ll Love It Here Please Note: the following benefits are for salaried employees - Hybrid work (SF office Mon/Tues/Thurs) + catered lunches (Bay Area Positions only) - Competitive salary, equity, and 401(k) - Wellness stipend & great benefits (medical, dental, vision) - Generous PTO & parental leave - Bi-annual offsites & a collaborative, mission-driven culture What to Expect in the Interview Process - Apply & meet our recruiting team - Virtual interviews to showcase your skills - Final onsite loop to meet the team and get to know us better - Chat with our CEO Curious to Learn More? - Read our Blog https://www.infinitus.ai/blog/ to hear from Infinauts about what we’re building - Discover how our company values (CODES https://www.infinitus.ai/careers/) guide us - Follow our CEO, Ankit Jain https://www.linkedin.com/in/jainankit/recent-activity/all/, for industry updates We’re building AI agents that tackle healthcare’s toughest problems and open new possibilities. Ready to join us? Let’s talk! Infinitus Systems is committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. Infinitus Systems believes that diversity and inclusion among our teammates is critical to our success as a global company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. Please Note: Applicants must be authorized to work in the US without employer sponsorship.
High-throughput data generation to advance ML desi...
At Inceptive, you will drive development forward that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software. Our AI models learn to generate therapeutic molecules with improved properties by training on natural and experimentally-derived data. Acquiring data relevant to function at scale is a critical step in maximizing the performance of our models. We think broadly about the type and scale of data necessary to improve our models, then identify or invent the methods needed to acquire that data. You will be responsible for the development and deployment of novel high-throughput assays to measure various properties of large sequence libraries. You will use a data-driven approach to optimize assays and apply chemical and biological insights to maximize the utility of information collected. You will apply this data to efficiently improve design of therapeutic molecules in close collaboration with biologists, ML and data engineers, and translational experts. Your Mission, should you choose to accept it - Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise - Collaborate with team members from diverse backgrounds to create experiments that creatively leverage biology and computation - Develop and execute pooled assays to measure sequence-to-function in vitro, in cells, and in vivo - Generate, analyze, and communicate data that maximally impacts AI-based molecular design Qualifications - PhD and 4+ years of post-PhD experience (e.g., startup, industry, or research) - Problem-solver who combines deep knowledge of experimental methods with quantitative intuition to generate biological data at and beyond the state-of-the-art - Solid foundation in theory and techniques of molecular and cellular biology - History of building highly multiplexed assays to generate rich datasets from mammalian cells, such as large functional screens or single-cell ‘omics - Scientific programming (preferably in Python), including analysis and visualization of complex data - Availability to work with team members across US and Europe, with meetings starting at 8am PT - Readiness to travel several times a year for company retreats and business events - We value in-person collaboration and expect candidates to work at our lab location Preferred skills - Experience with mammalian synthetic biology, particularly for cell therapy applications - Knowledge of RNA biology, biochemistry, and biologics drug development - Strong understanding of next-generation sequencing platforms (Illumina, Oxford Nanopore, Pac Bio), including library preparation and data analysis - Experience generating and analyzing large ‘omics datasets, via sequencing and/or mass spectrometry Compensation $135K – $240K + Bonus + Equity What we offer - A competitive compensation package - 30 days paid vacation per year - Comprehensive health insurance for US based Beginners - 401K with company match for US based Beginners and Direktversicherung for German Beginners - Quarterly company-wide retreats - Monthly wellness benefit - Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland - Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth - A buddy to help you get settled *Varies by country and does not apply to internships At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming antedisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields. We approach our goals with a Beginner's mind, humbly and with fresh eyes, and aim to become the pioneers of a new discipline rooted in biology as much as in deep learning, whose impact will be realized together with out-of-the-box thinkers in business and entrepreneurship, defying established categorizations. We are building a company culture centered around growth, learning, and discovery. We believe in humility and open-mindedness in how we approach each other, as well as problems we don't yet have solutions for. It is the policy of Inceptive to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Inceptive prohibits any such discrimination or harassment. Inceptive is also committed to welcoming and providing accommodations to people with disabilities. Please let us know if you need any accommodations throughout your application process.
Low-Level Senior Software Engineer, Xet Storage -...
At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github. About the Role Roles at Hugging Face are very fluid and dynamic -- we're looking for someone who is comfortable taking on different challenges that evolve over time. This role sits on the Xet Storage team, the group responsible for the storage system behind all of Hugging Face. Today we store over 200PB (and growing rapidly!) of the world's most important ML & AI assets. Xet is the underlying storage architecture for the entire Hugging Face platform and community -- from the largest model repositories to the datasets and Spaces that millions of people build on every day. In this role, you'll work across two closely connected surfaces. You'll contribute to xet-core , our open-source project written in Rust that powers hf-xet -- the Python library underpinning the Hugging Face Hub client and the wider ecosystem of open-source tools the community relies on. And you'll design, build, and operate meaningful and challenging features in the Xet Storage backend, contributing to the broader Infrastructure organization at Hugging Face. We're a small team building and operating incredible things at enormous scale, in a high-trust, low-process, async, and remote environment -- and we lean heavily on the latest AI tools to move fast. If you love writing low-level, high-performance code and are energized by the challenge of large-scale, scalable services, this is the team for you. This usually means proven experience building and operating production systems software, but we consider every applicant on an individual basis. Requirements What we're looking for 8+ years building and scaling distributed systems, storage, or networking infrastructure. Proficiency in a low-level systems language, with Rust strongly preferred (we also work in Python, Typescript, Go, and C++ across the stack). A track record of working independently in a high-trust, low-process environment -- you're comfortable with ambiguity and take ownership end to end. Comfort operating in a fast-moving, async, and fully remote environment. A passion for building simple, robust, and scalable systems relied on by engineering and science teams around the world. Bonus points if you have Experience designing efficient, high-performance, fault-tolerant data storage and retrieval systems. Experience operating production systems -- monitoring, alerting, and distributed debugging and recovery. Familiarity with git internals, cloud infrastructure (AWS, Azure, GCP, Kubernetes), databases (relational and non-relational), or networking. About You If you love open-source, are excited by the intersection of low-level performance work and large-scale services, and want your code to sit at the foundation of the world's largest platform for AI builders, then we can't wait to see your application! If you're interested in joining us, but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact. One more thing At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “ GPU-poor and proud 🤗”. No trick, no catch, it just tells us a real person is on the other side. Benefits More about Hugging Face We are actively working to build a culture that values diversity, equity, and inclusivity . We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education. We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off. We support our employees wherever they are . While we have office spaces in NYC and Paris, we're very distributed and all remote employees have the opportunity to visit our offices. If needed, we'll also outfit your workstation to ensure you succeed. We want our teammates to be shareholders . All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside. We support the community . We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.
Low-level Senior Software Engineer, Xet Storage -...
At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github. About the Role Roles at Hugging Face are very fluid and dynamic -- we're looking for someone who is comfortable taking on different challenges that evolve over time. This role sits on the Xet Storage team, the group responsible for the storage system behind all of Hugging Face. Today we store over 200PB (and growing rapidly!) of the world's most important ML & AI assets. Xet is the underlying storage architecture for the entire Hugging Face platform and community -- from the largest model repositories to the datasets and Spaces that millions of people build on every day. In this role, you'll work across two closely connected surfaces. You'll contribute to xet-core , our open-source project written in Rust that powers hf-xet -- the Python library underpinning the Hugging Face Hub client and the wider ecosystem of open-source tools the community relies on. And you'll design, build, and operate meaningful and challenging features in the Xet Storage backend, contributing to the broader Infrastructure organization at Hugging Face. We're a small team building and operating incredible things at enormous scale, in a high-trust, low-process, async, and remote environment -- and we lean heavily on the latest AI tools to move fast. If you love writing low-level, high-performance code and are energized by the challenge of large-scale, scalable services, this is the team for you. This usually means proven experience building and operating production systems software, but we consider every applicant on an individual basis. Requirements What we're looking for 8+ years building and scaling distributed systems, storage, or networking infrastructure. Proficiency in a low-level systems language, with Rust strongly preferred (we also work in Python, Typescript, Go, and C++ across the stack). A track record of working independently in a high-trust, low-process environment -- you're comfortable with ambiguity and take ownership end to end. Comfort operating in a fast-moving, async, and fully remote environment. A passion for building simple, robust, and scalable systems relied on by engineering and science teams around the world. Bonus points if you have Experience designing efficient, high-performance, fault-tolerant data storage and retrieval systems. Experience operating production systems -- monitoring, alerting, and distributed debugging and recovery. Familiarity with git internals, cloud infrastructure (AWS, Azure, GCP, Kubernetes), databases (relational and non-relational), or networking. About You If you love open-source, are excited by the intersection of low-level performance work and large-scale services, and want your code to sit at the foundation of the world's largest platform for AI builders, then we can't wait to see your application! If you're interested in joining us, but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact. One more thing At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “ GPU-poor and proud 🤗”. No trick, no catch, it just tells us a real person is on the other side. Benefits More about Hugging Face We are actively working to build a culture that values diversity, equity, and inclusivity . We are intentionally building a workplace where people feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education. We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off. We support our employees wherever they are . While we have office spaces in NYC and Paris, we're very distributed and all remote employees have the opportunity to visit our offices. If needed, we'll also outfit your workstation to ensure you succeed. We want our teammates to be shareholders . All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside. We support the community . We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.
Senior Software Engineer
SENIOR SOFTWARE ENGINEER ABOUT THE ROLE Hippocratic AI's AI agents are already working inside real hospitals and health systems — this role owns the backend infrastructure that keeps them fast, reliable, and ready to scale as that footprint grows. You'll architect systems built for tomorrow's volume, not just today's, working closely with data scientists, ML engineers, and product managers to turn healthcare requirements into production-grade infrastructure. WHAT YOU'LL DO Build Scalable, Reliable AI Infrastructure - Architect backend systems that sustain 99.9%+ uptime for high-volume healthcare data and LLM processing as usage grows exponentially - Implement monitoring that surfaces issues before they reach production AI agents - Own performance and reliability improvements across backend systems in collaboration with data scientists and ML engineers Engineer Data Pipelines for Healthcare AI - Design data pipelines that ingest, process, and prepare large-scale, multi-modal (speech, vision, text) healthcare datasets for training and inference with minimal latency - Build tag management and metadata systems that make large datasets organized and retrievable - Develop and optimize infrastructure supporting data ingestion, feature extraction, and tagging workflows Ship APIs and ML Enablement - Develop APIs and microservices that reduce processing time and improve responsiveness for AI model interaction and data retrieval - Build infrastructure that makes ML workflows reproducible end-to-end, from data preparation through model deployment - Accelerate time-to-production for new AI capabilities LOCATION AND TRAVEL We believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Menlo Park office five days a week. WHAT YOU BRING MUST-HAVE - Bachelor's degree in Computer Science, Computer Engineering, or a related field (Master's preferred) - 4+ years of backend development experience using Python, Golang, or similar languages - Experience building and maintaining multi-modal (speech, vision, text) data pipelines using Ray, Apache Airflow, or similar for distributed processing and model experimentation, including distributed computing frameworks like Spark or Hadoop - Familiarity with relational database systems and RESTful APIs - Basic understanding of cloud infrastructure (AWS, GCP, or similar) NICE-TO-HAVE - Exposure to AI/ML concepts or experience working with LLMs - Experience working in teams that handle sensitive or regulated data - Familiarity with gRPC, GraphQL, or similar - Experience with real-time audio - Exposure to DevOps concepts — CI/CD, deployment, Terraform, build systems - Experience with data science WHAT SUCCESS LOOKS LIKE Within 6-12 months, the backend systems you've built or hardened are sustaining 99.9%+ uptime under exponential growth in healthcare data and LLM traffic. New AI capabilities move from data preparation to production faster because the ML workflows and pipelines you designed are reproducible end-to-end. Your monitoring catches issues before they ever reach a live AI agent in a hospital setting. WHY JOIN HIPPOCRATIC AI Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation. Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA. Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others. Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative. EQUAL OPPORTUNITY Hippocratic AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, genetic information, military or veteran status, or any other characteristic protected by applicable law. We are committed to building a team that reflects the patients we serve. We actively encourage applications from candidates of all backgrounds. If you require accommodations during the hiring process, please contact people@hippocraticai.com. Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com http://hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.
Forward Deployment Engineer (Residency Program)
ROLE MISSION As HAI's Forward Deployed Engineer (FDE) Resident, you will own the delivery of safe, autonomous clinical conversations with patients, from the conversation layer to the integration design. You'll develop and refine the prompts and conversation logic that determine how millions of patients experience our breakthrough healthcare AI. And you’ll architect the transports and mappings to get data in and out of these conversations. This role exists because building truly autonomous clinical conversations requires both deep technical skill and relentless focus on patient experience—and we need someone who can master both. WHAT YOU WILL ACCOMPLISH Own your first major outcome: By day 90, you will have shipped improvements to at least two live conversation workflows, developed advanced prompts that meaningfully improve clinical safety scores or patient satisfaction metrics, collaborated with clinicians to translate their feedback into conversation logic, and shipped code that's now running in production healthcare environments. Drive lasting impact: This is the front door to our Forward Deployed Engineer (FDE) track: your first 6 months are as an FDE Resident, followed by 6 months as an Associate FDE, working alongside FDE leadership with exposure to Product Engineering and AI Engineering along the way. Most residents graduate into full FDE roles, with some moving into Engineering or Product based on their strengths and interests. THE TEAM You'll work alongside software engineers, ML scientists, product managers, and clinical experts who are obsessed with getting conversation right. This is a collaborative team that ships fast, values experimentation, and treats patient safety as non-negotiable. You'll have direct input into product decisions and the autonomy to innovate on conversation and integration design. WHAT YOU WILL DO - Develop advanced prompts for our conversation planning layer using sophisticated prompting techniques (chain-of-thought, few-shot learning, role-based prompting, structured outputs) to enable complex agentic workflows that handle real clinical scenarios - Engineer conversation logic and patient interactions that balance clinical accuracy, safety guardrails, and patient experience—writing, testing, and iterating on prompts that make our agents feel natural and trustworthy - Design and build the integrations that connect our conversational agents to customer EHRs, scheduling systems, and telephony platforms—turning HL7/FHIR feeds and REST/webhook APIs into the real-time signals that shape every conversation - Collaborate with clinicians, product managers, and engineers to translate clinical requirements into conversation designs, conduct user testing with healthcare professionals, and iterate based on feedback from real-world usage - Conduct rigorous experiments and analysis on model outputs, prompt variations, and conversation strategies—measuring impact on clinical safety scores, patient satisfaction, task completion rates, and other key metrics - Use advanced prompting techniques including retrieval augmentation, tool calling, conditional logic, and multi-turn conversation management to optimize model performance and patient experience across diverse clinical scenarios - Maintain and improve our conversation codebase, ensuring prompts are version-controlled, documented, and deployed safely to production healthcare environments with proper testing and rollout procedures - Sit shoulder-to-shoulder with customer engineering teams during go-lives, debugging integration issues live and turning one partner's edge case into a reusable pattern that ships to every future customer LOCATION REQUIREMENT We believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Menlo Park office five days a week, unless otherwise specified. BASIC QUALIFICATIONS - Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related technical field (or equivalent demonstrated coursework and professional projects) - 2+ years of professional industry experience in software development, AI/ML, or related technical roles - Strong Python proficiency with hands-on experience writing production or near-production code - Demonstrated experience with LLM prompting through professional work or substantial personal projects (ChatGPT, Claude, or similar models) - Experience building integrations with databases and RESTful APIs, including understanding of async patterns and error handling - Strong problem-solving mindset with proven ability to break down complex problems and iterate toward solutions PREFERRED QUALIFICATIONS - Experience with backend development frameworks (Flask, Django, FastAPI, Spring Boot, or similar) - Portfolio of personal or academic projects demonstrating full-stack development, AI experimentation, or prompt engineering work - Familiarity with AI/ML concepts including model architectures, training approaches, or evaluation methods - Understanding of data privacy, security, and compliance best practices, particularly in regulated healthcare environments (HIPAA, healthcare data handling) - Healthcare or health-tech experience, including exposure to clinical workflows, EHR systems, or patient-facing applications - Experience with prompt engineering frameworks or tools (LangChain, LangSmith, Anthropic SDK, etc.) WHY JOIN HIPPOCRATIC AI Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation. Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA. Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others. Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative. EQUAL OPPORTUNITY Hippocratic AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, genetic information, military or veteran status, or any other characteristic protected by applicable law. We are committed to building a team that reflects the patients we serve. We actively encourage applications from candidates of all backgrounds. If you require accommodations during the hiring process, please contact people@hippocraticai.com. Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com http://hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.
Associate Chief Nursing Officer
ABOUT US Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs as part of our Polaris constellation, resulting in a system with over 99.9% accuracy. WHY JOIN OUR TEAM Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation. Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA. Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others. Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative. ABOUT THE ROLE As Associate Chief Nursing Officer, you will collaborate directly with the Chief Nursing Officer to lead nursing operations, client partnerships, and assist with our AI product development. Our nursing team plays a critical role in setting clinical standards for Voice AI Agents, ensuring patient interactions are able to operate at the highest quality of care, and supports AI product development for the nursing profession. This role will own day-to-day nursing operations across both our production and evaluation environments including managing a team of nurses. In addition to overseeing operations, the successful candidate will represent nursing expertise directly with clients, translate clinical realities into product requirements, and help shape the future of our AI-powered nurse co-pilot, and other AI tools. This is an opportunity for an experienced nursing leader who is excited about the potential of AI to extend the reach of great nursing care—and who wants to help build the infrastructure that makes it possible. WHAT YOU'LL DO Nursing Operations Leadership - Own and oversee all nursing operations across both production and evaluation environments, ensuring consistent quality, safety, and efficiency. - Establish and maintain agentic clinical protocols, workflows, and quality standards that align with regulatory requirements and Hippocratic AI's patient safety commitments. - Monitor team performance, drive continuous improvement, and create a culture of clinical excellence and accountability. - Serve as a clinical counterpart to engineering, data science, and go-to-market. Translate nursing domain expertise into technical requirements, shape the AI training data strategy, and support enterprise sales cycles with clinical credibility. - Be a public face for the company, including representing the company at national nursing conferences, take on media and public speaking opportunities and publish on the future of AI and nursing operations, growing the company's reputation as the most trusted clinical partner in AI-enabled nursing. Client Partnership & Subject Matter Expertise - In collaboration with the Chief Nursing Officer, serve as the nursing voice in customer meetings and executive engagements, representing clinical expertise with confidence and authority. - Partner with the sales, customer success, and clinical teams to understand client needs, address nursing-related questions, and build trust with health system partners. - Act as a subject matter expert on nursing practice, workflows, and scope of care across diverse clinical settings. - Help prospective and current clients understand how Hippocratic AI's technology integrates with existing nursing and clinical workflows. Product Development & Nurse Co-Pilot Mapping - Collaborate with product and engineering teams to translate nursing knowledge and operational insights into product requirements and feature priorities. - Contribute to the development and refinement of nursing-specific AI capabilities, ensuring clinical accuracy, appropriate scope, and real-world usability. - Collaborate with the Chief Nursing Officer on the mapping and design of the nurse co-pilot product, defining use cases, interaction patterns, and clinical guardrails in partnership with the product team. - Lead continuous discovery with CNOs, nurse managers, and bedside nurses. Build and maintain a deep understanding of care model economics, workforce dynamics, documentation burden, and scope-of-practice constraints that shape product-market fit. - Partner with client health systems to reimagine nursing operational models — staffing ratios, acuity-based assignments, shift handoff, and escalation protocols — powered by the company's AI platform. - Build and lead a nursing transformation practice, including playbooks, embedded implementation resources, and outcome measurement frameworks that enable health systems to sustain change post-deployment. Ensure internal nursing operations fit within this model and serve as an extension of transformational change. - Establish rigorous outcomes architecture by defining what success looks like, designing for measurability at build, and reporting on clinical and operational impact that validates the product narrative. WHAT YOU BRING Must Have: - Active RN license in good standing; BSN required. - 10+ years of nursing leadership experience with at least 5+ years of experience across diverse care settings, including managing virtual workforce. - Direct P&L responsibility across multiple cost centers or operational lines is required - Leadership experience in nursing operations with responsibility for P&L management - Demonstrated experience working directly with non-clinical functions — product, engineering, data science, sales, or customer success. - Evidence of designing or scaling a clinical implementation, quality improvement, or workflow transformation program — not just managing within an existing one. - Exceptional communication and presentation skills, with comfort representing clinical perspectives to senior stakeholders and external clients. - Strong analytical mindset and the ability to translate complex clinical concepts into operational and product requirements. - Experience establishing or improving clinical protocols, workflows, or quality improvement programs. - Demonstrated track record of operational transformation in health systems - Ability to operate across clinical, technical, and executive contexts Nice to Have: - MSN, DNP, or equivalent advanced nursing degree. - Minimum 2+ years of nursing leadership experience outside of a traditional hospital or health system — specifically in a health-tech, digital health, AI/ML-enabled care, or clinical operations product company. - Track record of working effectively in fast-paced, ambiguous, cross-functional environments. - Experience building or scaling a clinical implementation function Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com http://hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process. WHY JOIN HIPPOCRATIC AI Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation. Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA. Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others. Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative. EQUAL OPPORTUNITY Hippocratic AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, genetic information, military or veteran status, or any other characteristic protected by applicable law. We are committed to building a team that reflects the patients we serve. We actively encourage applications from candidates of all backgrounds. If you require accommodations during the hiring process, please contact people@hippocraticai.com. Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com http://hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.
Director of Partnerships, AI Model and Ecosystem
Why work at Higgsfield AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $500M in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. About the role: Higgsfield AI is seeking a Director of Partnerships, AI Model and Ecosystem to lead strategic partnerships across our global compute ecosystem. This is a highly cross-functional role focused on identifying partnership opportunities, developing commercial strategies, negotiating agreements, and serving as the primary relationship owner for key infrastructure partners. You'll work closely with leadership, Finance, Marketing, Legal, Engineering, Product, and external executives to secure partnerships that enable Higgsfield's continued hypergrowth. The ideal candidate combines the structured problem-solving of a management consultant with exceptional relationship management and commercial negotiation skills. You are comfortable navigating ambiguity, aligning diverse stakeholders, and driving complex initiatives from strategy through execution. What You'll Do: Build Strategic Partnerships - Identify, evaluate, and develop strategic partnerships across cloud infrastructure, GPU providers, hardware vendors, and other compute partners. - Own relationships with key external partners from initial engagement through long-term account management. - Develop partnership strategies that align with Higgsfield's business objectives and infrastructure roadmap. - Identify opportunities to expand strategic partnerships over time. Lead Commercial Negotiations - Structure and negotiate commercial agreements that maximize long-term value. - Coordinate negotiations across Legal, Finance, Marketing, Product, and Engineering stakeholders. - Drive contract discussions through execution while balancing technical, operational, and commercial priorities. - Manage ongoing commercial relationships and partnership performance. Drive Cross-Functional Alignment - Serve as the central point of contact for strategic partnership initiatives. - Identify key internal and external stakeholders and align priorities across multiple organizations. - Understand partner motivations, business objectives, and decision-making processes. - Build consensus and remove blockers to accelerate partnership execution. Influence Business Strategy - Conduct market research and competitive analysis across the AI infrastructure ecosystem. - Develop business cases and executive-level recommendations for strategic partnerships. - Monitor industry trends and identify emerging partnership opportunities. - Support executive leadership with strategic planning and partnership reporting. Requirements: - 5–10 years of experience in management consulting, strategy, business development, strategic partnerships, corporate development, investment banking, or related experience. - Experience leading complex, cross-functional strategic initiatives. - Strong commercial negotiation and contract management experience. - Exceptional executive presence and stakeholder management skills. - Demonstrated ability to navigate complex organizations and influence without direct authority. - Strong analytical and structured problem-solving skills. - Experience building business cases and presenting recommendations to executive leadership. - Excellent written, verbal, and presentation skills. - Ability to manage multiple high-priority initiatives in a fast-paced environment. - Experience working with Legal, Finance, Marketing, Product, and Engineering teams. - Experience within AI, cloud infrastructure, hyperscalers, semiconductors, GPU providers, enterprise technology, or adjacent industries. - Experience negotiating strategic technology partnerships or infrastructure agreements. - Background in management consulting (McKinsey, Bain, BCG, or similar), strategy, or corporate development. - Familiarity with AI infrastructure, cloud computing, or large-scale distributed systems. - Experience working at a high-growth, venture-backed technology company. Compensation & Benefits - We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth. - Base Salary: The anticipated salary range for this role is $250,000 - $350,000 depending on experience, skills, scope, and location. - Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program. - Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. - Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks.The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team. - Significant ownership, direct impact, and opportunities for professional growth as the company scales. This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams. Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.
Backend Engineer - Infrastructure
About HeyGen At HeyGen, our mission is to make visual storytelling accessible to all. Over the last decade, visual content has become the preferred method of information creation, consumption, and retention. But the ability to create such content, in particular videos, continues to be costly and challenging to scale. Our ambition is to build technology that equips more people with the power to reach, captivate, and inspire audiences. Learn more at www.heygen.com . Visit our Mission and Culture doc here . Position Summary As a Backend Engineer (Infrastructure) at HeyGen, you'll spearhead the development of core systems and infrastructure crucial to powering our products. Your expertise will be instrumental in crafting scalable, reliable, and efficient backend systems tailored to accommodate our expanding user base. Key Responsibilities - System Development: Design, develop, and deploy scalable and efficient foundational systems. Examples include: - Data Infrastructure: Forge the next generation of data systems to fuel our analytics - Cloud Infrastructure: Multi-vendor GPU capacity management and scheduling - ML Infrastructure: Construct the ML training infrastructure to enhance our AI researchers’ productivity, and inference systems to optimize the scalability and performance of our video GenAI. - Product Infrastructure: Create the foundation for HeyGen product - Collaboration: Work closely with product engineers, AI researchers to deliver best performant systems. - Performance Monitoring: Monitor backend systems for performance, errors, and anomalies. Implement fixes and improvements as needed. - Code Quality: Maintain high code quality through regular code reviews, pair programming, and writing unit and integration tests. - Continuous Learning: Stay updated with the latest system technologies and best practices to ensure HeyGen remains at the forefront of technology. Qualifications - Bachelor's degree in Computer Science, Engineering, or a related field. - 2+ years of experience working on scalable and performant systems. - Proficiency in python or c++. - Experience with relational and NoSQL databases, such as PostgreSQL, MySQL, MongoDB. - Familiarity with cloud platforms like AWS, Azure, or GCP. - Strong knowledge of API design and development. Preferred Qualifications - Master’s degree in Computer Science, Engineering, or a related field. - Experience with container orchestration tools like Kubernetes. - Experience with Machine Learning Infrastructure especially computer vision. - Prior experience in a startup or fast-paced tech environment. What HeyGen Offers - Competitive salary and benefits package. - Dynamic and inclusive work environment. - Opportunities for professional growth and advancement. - Collaborative culture that values innovation and creativity. - Access to the latest technologies and tools. Salary Range $180,000 – 240,000 annually Please note that the salary information is a general guideline only. HeyGen considers factors such as scope and responsibilities of the position, candidate's work experience, education/training, key skills, and internal equity, as well as location, market and business considerations when extending an offer. As part of our total rewards package, HeyGen offers comprehensive benefits including a 401k plan, health benefits, generous PTO, a parental leave program and emotional health resources. HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Software Engineer, AI Agent
ABOUT HEX Hex is growing our team of builders on a mission to make everyone a data person. Our platform solves key pain points with today’s data and analytics tooling, and empowers anyone to explore data using natural language, with or without code, on trusted context. Thousands of customers like Ramp https://hex.tech/customers/ramp/, Figma https://hex.tech/customers/figma/, Stubhub https://hex.tech/customers/stubhub/, Anthropic, and Gamma love Hex https://www.g2.com/products/hex-tech-hex/reviews for our beautiful UI, agentic superpowers, and boundless flexibility. Hex has raised over $100M from leading investors like Sequoia, a16z, Snowflake and Amplify. With office hubs in San Francisco and New York, as well as remote team members throughout the US and UK, we’re a high-agency team that ships fast and has fun doing it. Check out our Intro to Hex video https://www.youtube.com/watch?v=qAXsnrNlavk and employee handbook https://www.notion.so/hexhq/Hex-Handbook-9fff0d42860e4f70815c599e0d1664d6 to learn more about what it’s like to work at Hex. ABOUT THE ROLE We are looking for senior and staff-level fullstack engineers eager to join the team building our leading Magic AI features. At Hex we're deeply focused on building powerful, integrated AI features that augment and accelerate analytics workflows. The possibilities here are incredible, and we're uniquely positioned to re-invent the way people think about understanding data. In this role, you’ll take the lead on building AI-powered features into Hex, partnering closely with our Research team on context and model prompting, and the rest of our product engineering teams on integrating into the platform. The fruits of your work will fundamentally change the way that many thousands of people work with data, and give you a front-row seat to the most exciting technological shift in our lifetimes. As part of our Agent Platform team, you’ll own the scalable agent infrastructure powering today’s most powerful data agents, as well as the cutting-edge experimentation tooling that allows the rest of the team to rapidly deliver new AI features in the product. WE'D LOVE TO HEAR FROM YOU IF YOU HAVE: - At least 4+ years of software engineering experience. - Proficiency with React and Typescript in addition to knowledge around architecture and systems design. - Experience leading and executing on major product initiatives. - Excitement for getting your hands dirty and diving deep into how the browser works to develop high-quality and performant user experiences. - An aptitude for how web infrastructure works to develop high-quality internal developer and external user experiences. - An instinct for strategic thinking and aligning with business and product goals while keeping a healthy balance of velocity and engineering excellence. - Interest in the data space, and a love of shipping great products and building tools that empower end users to do more. - Experience maintaining a high quality bar for design, correctness, and testing. - An ability to lead product initiatives while collaborating and mentoring fellow engineers. - Curiosity and an interest in diving into the bigger picture of building a company, including go-to-market, customer development, people, and marketing. This role will be hybrid (1-2 days per week) based out of our San Francisco, California headquarters or NYC office. OUR STACK Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack. The salary range for this role is: $198,750 - $295,000 In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off. The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process. By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.
Software Engineer, DevSecOps
Who we are Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations, cultivating an ambitious and committed team of mission-driven professionals to apply their skills to solve challenging problems. The role You will join the Platform Engineering team as a security-focused engineer responsible for embedding security into every layer of our developer platform and software delivery pipeline. You will own the security posture of our development environment — ensuring CMMC Level 2 compliance, hardening our software supply chain, and implementing the controls required for product teams to achieve ATO against NIST and other cybersecurity frameworks. You will work closely with platform and product engineers to build secure CI/CD pipelines, enforce policy-as-code, and maintain the shared infrastructure that all teams depend on. This role combines hands-on engineering with deep security expertise: you are not just auditing compliance, you are building the systems that make compliance automatic. The day-to-day - Deploying, updating, and securing Kubernetes workloads through ArgoCD and GitOps workflows - Building and maintaining secure CI/CD pipelines that enforce policy, scan for vulnerabilities, and produce auditable build artifacts - Maintaining and hardening shared services (GitLab, Artifactory, container registries) that the entire organization depends on - Implementing and enforcing security controls aligned with CMMC L2, NIST 800-171, and other frameworks required for ATO - Securing the software supply chain: image signing, SBOM generation, dependency scanning, and provenance tracking - Conducting threat modeling to surface architectural risks before they become incidents - Detecting, investigating, and responding to security incidents across infrastructure and applications - Working with product teams to ensure their workloads meet security and compliance requirements before and after deployment - Supporting the secure hosting of ML/AI workloads, including model training environments and sensitive data handling You should apply if you - Have 5+ years of experience in DevSecOps, security engineering, or infrastructure engineering with a security focus - Have a Bachelor's degree in Computer Science, Engineering, Cybersecurity, or a related field - Have deep experience with Kubernetes - deployment, networking, RBAC, pod and cluster security, and operational troubleshooting - Are proficient with ArgoCD or similar GitOps tooling for managing Kubernetes workloads at scale - Have strong experience writing and maintaining Helm charts - Are proficient in Python and Bash, with experience automating security and compliance workflows - Understand software supply chain security, including container image hardening, FIPS-validated cryptography, vulnerability scanning, SBOM, and artifact signing - Have hands-on experience implementing security controls from frameworks like NIST 800-171, NIST 800-53, or CMMC - Are comfortable with CI/CD pipeline design, particularly building in security gates, policy-as-code, and automated compliance checks - Have working knowledge of AWS and can collaborate effectively on infrastructure decisions - U.S. citizenship required Nice to have - Experience with Go or other systems programming languages - Experience shepherding systems through an ATO process - Familiarity with DISA STIGs and the Risk Management Framework (RMF) - Familiarity with Terraform and infrastructure-as-code for cloud resources - Experience with Nix or NixOS - Experience with SIEM platforms (e.g., Elastic) and security monitoring/incident response - Experience securing and deploying ML/AI workloads — GPU environments, training pipelines, data classification - Red teaming or penetration testing experience - Certifications such as CKS, Security+, or CISSP - Experience in defense, intelligence, or other regulated environments Join Helsing and work with world-leading experts in their fields - Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns - The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world - Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defense industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward - In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts - We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practice responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about What we offer - A focus on outcomes, not time-tracking - A generous compensation and benefits package (in addition to base salary) that includes, but may not be limited to, insurance coverage (medical and travel), flexible paid time off, paid holidays, and remote and/or hybrid work available depending on position. All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time. Helsing is an Equal Opportunity Employer. We will consider all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, genetics, or any other characteristic protected by applicable federal, state, or local law. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. Helsing's Candidate Privacy and Confidentiality Regime can be found here .
Software Engineer - Autonomous Air Systems
Who we are Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards. As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously. We are an ambitious and committed team of engineers, AI specialists and customer-facing program managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications. The role You’ll build the autonomy brain for a cutting-edge autonomous aerial platform that will actually take flight. At Helsing, you won't just be developing software; you'll be integrating state-of-the-art reinforcement learning agents into the operational systems of our own Unmanned Combat Aerial Vehicle (UCAV), the CA-1 Europa, part of the groundbreaking Centaur project. This is a unique opportunity to directly contribute to a novel autonomous system designed from the ground up. Working at the intersection of machine learning and systems engineering, you'll integrate reinforcement learning agents into high-performance runtime systems, enabling real-time autonomous decision-making in flight. This isn't theoretical; your code will enable the CA-1 Europa to perceive, reason, and act autonomously in the most demanding environments. What we build ultimately ends up in the hands of real people in high-risk, high-stress situations, so it must be both reliable and frictionless. To give some examples: - Autonomous Decision-Making Systems — reliable pipelines from sensor data to RL inference to tactical execution, including edge-case and failure-mode handling. - Reinforcement Learning Integration — bridging Python-based RL agents with Rust runtime systems for low-latency, reproducible inference. - Distributed Systems & Communications — handling intermittent connectivity and bespoke hardware protocols. - Training Infrastructure — distributed training, evaluation pipelines, and large-scale runs on custom simulators. In some areas, we're working at the state-of-the-art—actively implementing research papers and pushing further. In others, we're applying proven techniques to real-world situations they've never encountered before. Both require skill, diligence, and deep technical understanding. Our software operates under significant constraints, in constantly-changing environments, for users in high-risk situations. It must be reliable and frictionless. That's what makes this work hard—and worth doing. The day-to-day - Maintain our existing software stack, including working with internal and external customers to identify issues, improving operational reliability and performance, and fending off technical debt. The stack is a mix of Rust and Python, with Python mainly living in the ML-heavy sections. - Further develop our tests and benchmarks, both at the micro and macro level, including hardware-in-the-loop (HIL) simulations and flight testing. We operate in a domain where robustness is of the utmost importance, and an extensive and ever-improving test suite is key to achieving that. And without thorough benchmarks, we would be flying blind. - Review code contributions, proposals, and RFCs from colleagues, ensuring robustness and adherence to safety and performance standards critical for airborne applications. At Helsing we strongly believe that unblocking others takes precedence over spending more time on your own work. - Propose and implement new features, capabilities, algorithms, infrastructure, or even full products across our stack, with a focus on refining the capabilities and reliability of our airborne mission systems. We encourage our engineers to look beyond their immediate team for missed opportunities, and to speak up when they identify one. - Become a mentor, find a mentee, and help support and develop our interviewing pipeline. The people make or break the company, and we want as many engineers as possible to be part of fostering and growing the organisation. - Share your experience and technical know-how with other Helsingers. We host tech talks, get together for smaller “let’s learn together” groups, run topical office hours (e.g., on Rust), etc. to help each other get better with time. You should apply if you - Can write legible, maintainable, and performant code. - Communicate well in English, both verbally and in writing. - Enjoy collaborating with others, including reviewing code and pair programming, particularly on complex system architectures involving tight hardware-software integration on a real-world aerial platform. - Are comfortable working asynchronously (writing PRs and RFCs, having discussions by email). - Have strong backend or embedded development experience, ideally with a language like Rust, Go, or C++. - Feel comfortable working with Python with the ML-heavy sections of the stack. - Strive to improve yourself, your peers, and the culture you work in over time. - Feel like ethical considerations are an inherent part of engineering. Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points. Nice to have - Rust and Python specifically. - Experience in deploying Reinforcement Learning or Machine Learning agents in real-world systems - Safety Programming Experience - Familiarity with low-level flight control systems and their interfaces, even if not directly developing them. - Experience with sensor integration (IMUs, GPS, Lidar, Cameras) and sensor fusion techniques for navigation. - Robotics (e.g., control systems). - Production ML systems. - Hardware interfaces (e.g., Arduino). Join Helsing and work with world-leading experts in their fields - Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns - The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world - Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward - In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts - We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about What we offer - A focus on outcomes, not time-tracking - Competitive compensation and VSOP options - Relocation support - Social and education allowances - Regular company events and all-hands to bring together employees as one team across Europe Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. Helsing's Candidate Privacy and Confidentiality Regime can be found here .
Multimodal Sensing Test Engineer
Who we are Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards. As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously. We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications. The role You will sit in the Optics Cluster of the Test Department, with a scope that crosses cluster boundaries. Sensing subsystems are not purely optical problems. They sit at the intersection of optics, electronics, embedded software, and mechanical integration. An EO camera in perfect focus but misaligned with the LiDAR produces dangerous data. An LWIR sensor that passes standalone characterisation but fails next to a hot avionics bay tells a different story on the airframe. You will act as a sensing system architect for test. You will translate sensing requirements into structured test cases, specify the optical, electrical, and mechanical ground support equipment (OGSE, EGSE, MGSE) needed to run them, and serve as the department's technical authority on sensor synchronisation, calibration, and multimodal data quality. Your work covers the full lifecycle: prototype characterisation, production acceptance, supplier evaluation, and in-service root cause analysis. The truth is in the field. The day-to-day - Characterise EO systems: MTF, SNR, dynamic range, distortion, vignetting, and spectral response, using collimators, integrating spheres, resolution targets, and calibrated light sources. - Characterise LWIR systems: NETD, spatial resolution, uniformity, and dynamic range with calibrated blackbodies, including the impact of self-heating across the operational temperature range. - Characterise LiDAR systems: range accuracy and precision, angular resolution, detection probability, and false-alarm rate under representative ambient light, target reflectivity, atmospheric, and vibration conditions. - Specify, procure, commission, and maintain OGSE, EGSE, and MGSE. Own calibration traceability. - Run temporal synchronisation campaigns across EO, LWIR, and LiDAR. Characterise trigger latency, PPS accuracy, and timestamp drift over mission duration. - Execute intrinsic, extrinsic, and temporal calibration across modalities. Design multi-modal fiducial targets visible to EO, LWIR, and LiDAR at once. Assess calibration stability after thermal cycling, vibration, and simulated ageing, and set re-calibration intervals for production. - Produce first-article characterisation reports for new sensor deliveries. Evaluate alternative sensor configurations to support design trade-offs. - Develop and supervise acceptance test procedures for production units within required cycle time. Monitor yield for systematic trends and initiate non-conformance where needed. - Assess new sensor suppliers. Review datasheets and qualification reports, characterise engineering samples, define qualification test campaigns, and produce supplier qualification reports. Act as the test department's technical contact for supplier engineering teams. - Investigate sensing failures reported from fielded products. Reproduce failures in the lab, isolate root cause across sensor, calibration, software, or integration, and verify corrective actions. - Feed validated sensor models, calibration parameters, and timing characterisations to the software team for the sensor fusion pipeline. Coordinate with the Environmental and Electrical clusters to sequence qualification correctly. - Keep test firmware and scripts under Git with clear branching, tagging, and release management. Produce validation records for critical test tools used in certification. Write documentation any engineer in the department can use without you present. You should apply if you Must have skills: - EO systems: quantitative grasp of MTF, SNR, dynamic range, spectral response, and radiometric calibration, with hands-on MTF measurement using slanted-edge or resolution target methods. - LWIR systems: quantitative grasp of NETD, spatial resolution, non-uniformity correction, and radiometric calibration with blackbodies. - LiDAR systems: understanding of ToF and FMCW principles, performance metrics, and characterisation methods. Experience with point cloud formats (ROS bag, PCD, or proprietary). - Sensor synchronisation and calibration: hands-on time-synchronisation of heterogeneous arrays using hardware triggers, PPS, and software timestamping, with quantitative verification. Intrinsic camera calibration in OpenCV, Kalibr, or equivalent. Extrinsic and temporal calibration across modalities. - OGSE, EGSE, MGSE specification, commissioning, and operation, including collimators, blackbodies, integrating spheres, precision optical mounts, and calibration targets. - Ability to derive test concepts that cover system-level behaviour of the integrated multimodal suite, not only individual sensors. - Requirements translation into traceable test cases with clear pass/fail criteria. Familiarity with Jama or DOORS is a plus. - Python (numpy, scipy, matplotlib, OpenCV) or MATLAB for data analysis. Qualifications: - Bachelor's degree (B.Sc. or B.Eng.) in a relevant engineering discipline such as optical engineering, photonics, electrical engineering (with a strong sensing or imaging component), applied or experimental physics, aerospace engineering (with a sensing or avionics component), mechatronics, or an equivalent technical field. M.Sc. in optical engineering, photonics, or a closely related field preferred. - At least 3 years of hands-on test engineering experience covering environmental, mechanical, or structural test. Direct experience with environmental chambers, vibration testing, and physical instrumentation is required. - Prior exposure to defence, dual-use, or regulated hardware is preferred. Experience under ITAR, EAR, or equivalent frameworks is an advantage. Note: We operate in an industry where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points. Nice to Have - Working knowledge of sensor fusion (Kalman filtering, point cloud registration) sufficient to derive calibration accuracy requirements. - ROS or ROS 2 for capture, timestamping, and replay in test. - Radiometric calibration methodology for quantitative EO and LWIR measurements. - GigE Vision, MIPI CSI-2, or USB3 Vision interface standards. - Photogrammetry or Structure-from-Motion for extrinsic calibration validation. Join Helsing and work with world-leading experts in their fields - Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns - The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world - Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward - In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts - We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about What we offer - Competitive salary and VSOP options - Relocation support : up to €2,500 and 4 weeks temporary accommodation - Learning : €500/£450 yearly allowance - Health & wellness : gym membership and mental health support (Nilo.health) - Social : regular company events and monthly social allowances - Enhanced parental leave : 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers - Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work - A hands-on onboarding program (affectionately labelled “Infraduction”), in which you will be building tooling and applications to be used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other engineering teams from day one Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. Helsing's Candidate Privacy and Confidentiality Regime can be found here .
Senior Product Operations Manager, Evaluation Qual...
WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW We’re looking for a senior operator to own the quality bar behind Harvey’s human evaluations. As we scale globally, the volume of eval work is growing 10x, but volume only matters if the output is trusted. This role makes Human Data’s signal decision-grade: rigorous, calibrated, and reproducible enough that Product, Engineering, and AI Research act on it to ship. As a member of our Evaluation Operations team, you’ll work alongside our Evaluation Operations Manager (who runs throughput and coordination) and partner closely with Applied Legal Researchers, Product, Engineering, and AI Research. You'll set the standard for what "good" looks like across eval data and methodology, and own the data analyses to make conclusions that teams will rely on, building the stakeholder trust that lets EPD act on the signal. WHAT YOU'LL DO - Own the quality bar for Harvey’s human evaluations: define what “good” looks like for eval methodology and data analysis, and produce decision-grade outputs for EPD - Author and maintain the evaluation guidelines, instructions, and databases that contract attorneys work from - Standardize and streamline rubric and evaluation design into repeatable templates and one documented methodology, partnering with Applied Legal Research (ALR), who supplies feature-specific legal depth - Own contract-attorney quality: onboarding, calibration training, inter-rater reliability, and the feedback loop (including benchmarks and gold references) that keeps judgment consistent across attorneys and over time - Conducting quantitative and qualitative statistical analyses, diagnosing error states, investigating root causes, and turning raw eval results into a structured, prioritized signal Product and ALR can act on - Run QA on vendor and contract-attorney deliverables against a defined bar before results inform a launch decision - Ensure the quality bar holds across jurisdictions and non-English geographies as coverage expands - Establish one standard, documented way to analyze eval results, and build lightweight operational dashboards to track rater capability and eval-program health - Support ALR in a review step that certifies an evaluation is sound before it scales to contract attorneys - Partner with ALR and Analytics to determine where human eval aligns with online signal and where it can provide expanded insights WHAT YOU HAVE - 6+ years in product operations, research operations, evaluation/QA operations, or quality program management - A track record of owning quality inputs (guidelines, instructions, benchmarks, QA procedures) for complex, expert-driven or human-in-the-loop work - Experience onboarding, training, and calibrating a distributed pool of expert raters, annotators, or reviewers, and running the feedback loop that improves their quality over time - Enough grounding in measurement concepts (calibration, inter-rater reliability, sampling, rubric design) to independently set up and own the quality of our evaluation loop yourself - Experience with running quantitative and qualitative data analyses, interpreting and running statistical tests on evaluation data (natively or with AI tool support), and communicating conclusions to various stakeholders - A record of scaling and streamlining evaluation quality processes under shipping pressure, with a bias toward documentation and reproducibility over one-off analysis - Ability to work deeply with domain experts (e.g., ALR / lawyers) and translate nuanced judgment into repeatable, documented standards - Strong cross-functional coordination across Product, Engineering, Research, ALR, and data providers/vendors - Clear communicator who can build credibility and trust with stakeholders - Bias to action and high ownership, from writing the guideline to auditing a vendor batch line by line BONUS POINTS - Experience in legal tech or working with domain experts in regulated industries - Experience owning quality across multiple markets, languages, or jurisdictions - Built calibration, inter-rater reliability, or capability-tracking systems for annotation or evaluation pipelines - Experience transitioning evaluation work in-house or otherwise improving evaluation ROI - Familiarity with LLM-as-judge / automated evaluation used alongside human eval - Early employee at a hyper-growth startup, or experience at a world-class product or platform operations org COMPENSATION $155,400 - $233,200 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-CD1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Data Scientist, Product
WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function. You will partner with Product, Engineering, Design, Go-to-Market, and company leadership to define how we measure product success, understand user behavior, and make high-quality decisions in a fast-moving environment. This role is both strategic and hands-on. You will define north-star and product-level metrics, design experiments and causal analyses, build source-of-truth reporting, and turn ambiguous product questions into clear recommendations. You should be comfortable operating where the data is imperfect, the product is evolving quickly, and the right answer requires both analytical rigor and strong product judgment. WHAT YOU'LL DO - Embed with Product and Engineering teams as a trusted analytical partner, identifying opportunities to improve user experience, adoption, retention, and business impact. - Define and maintain core metrics that create a shared understanding of product performance and customer value. - Design and evaluate experiments, including A/B tests and causal inference methods, to measure the impact of product, model, and workflow changes. - Analyze product usage, customer segments, and go-to-market signals to surface insights, size opportunities, and inform roadmap decisions. - Build dashboards, reports, and self-serve tools that help teams answer product questions with confidence. - Develop models, forecasts, and analytical frameworks to explain user behavior, detect anomalies, and guide prioritization. - Translate complex analyses into clear recommendations for technical, business, and executive audiences. - Partner with Engineering and Data teams to improve the infrastructure that powers analytics, experimentation, and decision-making. - Establish the standards, practices, and culture for Product Data Science at Harvey. WHAT YOU HAVE - 5+ years of experience in data science, product analytics, economics, statistics, or another quantitative field, ideally in a high-growth product company, AI company, research organization, or similarly ambiguous environment. - A strong track record of using SQL, Python, and statistical methods to answer product questions and turn analysis into product or business impact. - Experience defining new metrics and measurement frameworks from scratch, especially for products where usage patterns, customer value, or success criteria are still being discovered. - Deep fluency in experimentation, causal inference, A/B testing, and statistical modeling, with good judgment about when precision matters and when directional clarity is enough. - Strong product instincts and curiosity about how users adopt, evaluate, and expand their use of AI-enabled workflows. - Excellent written and verbal communication skills, including the ability to influence Product, Engineering, Go-to-Market, and executive stakeholders through clear reasoning and compelling data stories. - Comfort creating structure in fast-moving, ambiguous environments and raising the quality of decision-making for the teams. Bonus - Experience with AI/ML products, large language models, developer tools, enterprise software, or products used in complex professional workflows. - Experience as an early data science or analytics hire at a hyper-growth startup, including helping define team norms, tooling, and best practices. - Experience supporting enterprise or B2B products, including analysis of adoption, engagement, retention, expansion, or go-to-market motion. - Familiarity with modern data infrastructure and the practical tradeoffs involved in building reliable analytics in a rapidly evolving product environment. COMPENSATION $155,000 - $260,000 DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922]. #LI-SB1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Software Engineer II, Reinforcement Learning Envir...
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. WHY JOIN HANDSHAKE NOW: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue ABOUT HANDSHAKE AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. We are building our India team to help accelerate the development of frontier models. This team is a critical, strategic investment for us - we have grown the team 3x in the past six months to help fuel our next phase of growth. India-based teammates will work hand-in-hand with US-based teams to scope, execute, and deliver critical human data projects to Frontier Labs and other customers. ABOUT THE ROLE We're hiring a Software Engineer II to help build our Reinforcement Learning Environments (RLE) platform—the interactive systems where frontier AI models learn to complete real-world work. RLE environments simulate end-to-end workflows across domains like software engineering, finance, legal research, and business operations with realistic tools, constraints, and feedback loops. The interaction data generated powers the training and evaluation of the world's leading AI models. As part of our growing engineering organization in India, you'll partner closely with Engineering, Research, Product, and Operations teams in the US to build the platforms powering the next generation of AI. You'll own meaningful technical projects, contribute to platform architecture, and help build reliable systems that enable researchers to rapidly develop and evaluate frontier AI models. Location: Bengaluru, India. This is an in-office role. WHAT YOU'LL DO - Design, build, and scale our Reinforcement Learning Environments (RLE) platform and the infrastructure that powers it - Partner closely with Engineering, Research, Product, and Operations teams in the US to execute against a shared roadmap - Design and implement scalable backend services and data generation pipelines - Build modular environment domains that integrate seamlessly with model training and evaluation workflows - Improve platform reliability, observability, performance, and developer productivity - Participate in technical design discussions and contribute to architecture decisions - Write high-quality, maintainable code while helping improve engineering standards and best practices WHAT WE'RE LOOKING FOR - 6+ years of professional software engineering experience building backend systems, distributed systems, or platform infrastructure - Strong proficiency with TypeScript, React, and modern backend architectures - Strong understanding of PostgreSQL, data modeling, distributed systems, and system design - Experience building and operating production systems on AWS or GCP - Strong problem-solving skills and the ability to thrive in fast-moving, ambiguous environments - Experience collaborating effectively with globally distributed engineering teams, including teams based in the US NICE TO HAVE - Experience with reinforcement learning infrastructure, simulation systems, or AI evaluation platforms - Experience building internal developer platforms or workflow orchestration systems - Familiarity with Docker, Kubernetes, and CI/CD pipelines - Experience supporting applied ML or AI research teams - Experience working in a fast-growing startup or high-growth engineering organization WHAT SUCCESS LOOKS LIKE - Reinforcement Learning Environments become a trusted platform powering the next generation of AI model training - New environments launch quickly with high-quality, scalable infrastructure - Systems are reliable, observable, and built to support rapid iteration - You become a trusted engineering partner across the India and US teams, helping deliver critical platform capabilities You’ll Thrive Here If You: - Are motivated by solving operational problems that have direct, measurable impact. - Want to be part of a company shaping the future of AI through human data. - Can navigate ambiguity, act with urgency, and keep multiple workstreams moving in parallel. Perks: - Generous Equity Grant vested over 4 years - Housing Bonus: 1.3 Lakhs spread throughout the first year - Well Defined Performance Bonus ranging between 10 - 100% of base - Medical Insurance Coverage - Food credit for every in person day.
Senior Software Engineer, Coding
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. ABOUT THE ROLE We’re looking for a Senior Software Engineer to help build the systems that power high-quality coding data and evaluations for next-generation AI models. You’ll work on technically complex projects involving software engineering benchmarks, code review evaluation, agentic coding workflows, and developer-facing tools. You’ll combine strong engineering judgment with hands-on execution, designing reliable systems that enable teams to create, validate, and improve sophisticated coding datasets. This is an opportunity to shape foundational infrastructure at the intersection of software development and AI. You’ll operate with significant ownership, collaborate closely with engineers and technical program leaders, and help establish the standards and tools that support our fastest-growing AI initiatives. WHAT YOU'LL DO - Design, build, and operate scalable software systems for coding evaluation, data generation, and agentic development workflows. - Develop tools and services that analyze, validate, and improve AI-generated code. - Build reliable pipelines for code execution, testing, benchmarking, and quality measurement. - Partner with engineering, research, operations, and customer-facing teams to translate complex requirements into practical systems. - Drive technical decisions across architecture, APIs, data models, observability, and operational excellence. - Improve engineering velocity through reusable frameworks, automation, and developer tooling. - Lead projects from ambiguous problem definition through design, implementation, launch, and iteration. - Mentor engineers through design reviews, code reviews, and day-to-day collaboration. - Establish high standards for maintainability, correctness, security, and reliability. DESIRED CAPABILITIES - 5+ years of professional software engineering experience. - Strong proficiency in Python, JavaScript/TypeScript, Go, or another modern programming language. - Experience designing and operating production systems with meaningful scale, reliability, and performance requirements. - Strong understanding of software engineering fundamentals, including testing, APIs, data structures, distributed systems, and observability. - Experience building developer tools, infrastructure, data pipelines, evaluation systems, or other technically complex products. - Ability to work effectively in ambiguous environments and break large problems into clear, executable plans. - Excellent written and verbal communication skills, with the ability to explain technical tradeoffs to both technical and non-technical partners. - A track record of taking ownership and delivering high-quality results in collaboration with BONUS POINTS - Experience with AI/ML evaluation, coding agents, LLM applications, or developer productivity tools. - Familiarity with code execution sandboxes, GitHub workflows, CI/CD systems, or benchmark infrastructure. - Experience working with containerization, cloud platforms, databases, and distributed job orchestration. - Contributions to open-source software or a demonstrated passion for improving developer tools. - Experience partnering with research teams or customers to deliver technically rigorous solutions. PERKS Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, wellness stipend 📚 Growth: Learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
Senior Forward Deployed Engineer, Enterprise AI
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. ABOUT THE ROLE As a Forward Deployed Engineer at Handshake AI Enterprise, you'll embed directly inside enterprise customer environments as part of a small, expert team. You'll learn each customer's business deeply — their workflows, their bottlenecks, where the real leverage is — and translate that understanding into production-grade AI agents that measurably change how they operate. This isn't an implementation or consulting role. You'll own the full stack: defining the solution, building and deploying agents, designing evals, and iterating until performance actually moves. Over time, you'll become a genuine domain expert in your customer's vertical — and use that expertise to build AI that keeps getting better. If you've built AI that works in the real world and want to do it again at much higher stakes — with better data, closer lab relationships, and a founding team that moves fast — this is the role. - Embed directly with enterprise customers as part of a small deployment team, developing deep understanding of their business and workflows - Define AI-driven solutions based on real business needs — not theoretical use cases - Build and deploy production-grade agents tailored to specific customer use cases, owning end-to-end delivery - Design and run evals to measure agent performance; iterate and hill-climb until results move - Become a domain expert in your customer's vertical and use that expertise to build better AI over time - Work closely with Product and Platform engineers on your team to ship cohesive, reliable solutions - Establish engineering best practices, agent patterns, and reusable frameworks that help the forward-deployed team scale output without sacrificing quality - Surface insights from deployments that inform Handshake's platform and product roadmap Location: San Francisco, CA | 5 days / week in-office DESIRED CAPABILITIES - 5-6+ years of engineering experience, full-stack with strong backend depth - Real-world experience building and shipping AI applications in production — not just fine-tuning or prototyping - Strong understanding of agent architectures, evals, and how to measure and systematically improve AI performance - Comfort working directly with enterprise customers in ambiguous, high-stakes environments - Strong systems thinking — you can zoom out to the business problem and zoom in to the technical solution without losing either thread - High ownership mentality — you care about outcomes, not just outputs - Strong communication skills — you'll be in the room with senior stakeholders regularly and need to earn their trust quickly EXTRA CREDIT - Background at a company with a forward deployment or field engineering model - Experience building multi-agent systems in production - Domain expertise in a specific enterprise vertical (recruiting, finance, ops, legal, etc.) - Familiarity with enterprise security requirements, VPC deployments, or on-prem configurations - History of building evals infrastructure or AI quality measurement tooling PERKS Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend 📚 Growth: $2,000 learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
Senior Applied AI Engineer, Enterprise AI
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. ABOUT THE ROLE As an Applied AI Engineer at Handshake AI Enterprise, you'll embed directly inside enterprise customer environments as part of a small, expert team. You'll learn each customer's business deeply, their workflows, their bottlenecks, where the real leverage is, and translate that understanding into production-grade AI agents that measurably change how they operate. This isn't an implementation or consulting role. You'll own the full stack: defining the solution, building and deploying agents, designing evals, and iterating until performance actually moves. Over time, you'll become a genuine domain expert in your customer's vertical and use that expertise to build AI that keeps getting better. If you've built AI that works in the real world and want to do it again at much higher stakes, with better data, closer lab relationships, and a founding team that moves fast, this is the role. What You'll Do - Embed directly with enterprise customers as part of a small deployment team, developing deep understanding of their business and workflows - Define AI-driven solutions based on real business needs, not theoretical use cases - Build and deploy production-grade agents tailored to specific customer use cases, owning end-to-end delivery - Design and run evals to measure agent performance; iterate and hill-climb until results move - Become a domain expert in your customer's vertical and use that expertise to build better AI over time - Work closely with Product and Platform engineers on your team to ship cohesive, reliable solutions - Establish engineering best practices, agent patterns, and reusable frameworks that help the team scale output without sacrificing quality - Surface insights from deployments that inform Handshake's platform and product roadmap What We're Looking For - 5-6+ years of engineering experience, full-stack with strong backend depth - Strong applied AI engineering experience and backend depth - Real-world experience building and shipping AI applications in production, not just fine-tuning or prototyping - Strong understanding of agent architectures, evals, and how to measure and systematically improve AI performance - Comfort working directly with enterprise customers in ambiguous, high-stakes environments - Strong systems thinking, you can zoom out to the business problem and zoom in to the technical solution without losing either thread - High ownership mentality, you care about outcomes, not just outputs - Strong communication skills, you'll be in the room with senior stakeholders regularly and need to earn their trust quickly Location: San Francisco, CA | 5 days/week in-office Extra Credit - Background at a company with a forward deployment or field engineering model - Experience building multi-agent systems in production - Domain expertise in a specific enterprise vertical (recruiting, finance, ops, legal, etc.) - Familiarity with enterprise security requirements, VPC deployments, or on-prem configurations - History of building evals infrastructure or AI quality measurement tooling PERKS Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend 📚 Growth: $2,000 learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
Forward Deployed Engineer, Enterprise AI
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders - Build a massive, fast-growing business with billions in revenue About Handshake AI Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale. ABOUT THE ROLE As a Forward Deployed Engineer at Handshake AI Enterprise, you'll embed directly inside enterprise customer environments as part of a small, expert team. You'll learn each customer's business deeply — their workflows, their bottlenecks, where the real leverage is — and translate that understanding into production-grade AI agents that measurably change how they operate. This isn't an implementation or consulting role. You'll own the full stack: defining the solution, building and deploying agents, designing evals, and iterating until performance actually moves. Over time, you'll become a genuine domain expert in your customer's vertical — and use that expertise to build AI that keeps getting better. If you've built AI that works in the real world and want to do it again at much higher stakes — with better data, closer lab relationships, and a founding team that moves fast — this is the role. - Embed directly with enterprise customers as part of a small deployment team, developing deep understanding of their business and workflows - Define AI-driven solutions based on real business needs — not theoretical use cases - Build and deploy production-grade agents tailored to specific customer use cases, owning end-to-end delivery - Design and run evals to measure agent performance; iterate and hill-climb until results move - Become a domain expert in your customer's vertical and use that expertise to build better AI over time - Work closely with Product and Platform engineers on your team to ship cohesive, reliable solutions - Establish engineering best practices, agent patterns, and reusable frameworks that help the forward-deployed team scale output without sacrificing quality - Surface insights from deployments that inform Handshake's platform and product roadmap Location: San Francisco, CA | 5 days / week in-office DESIRED CAPABILITIES - 1-4+ years of engineering experience, full-stack with strong backend depth - Real-world experience building and shipping AI applications in production — not just fine-tuning or prototyping - Strong understanding of agent architectures, evals, and how to measure and systematically improve AI performance - Comfort working directly with enterprise customers in ambiguous, high-stakes environments - Strong systems thinking — you can zoom out to the business problem and zoom in to the technical solution without losing either thread - High ownership mentality — you care about outcomes, not just outputs - Strong communication skills — you'll be in the room with senior stakeholders regularly and need to earn their trust quickly EXTRA CREDIT - Background at a company with a forward deployment or field engineering model - Experience building multi-agent systems in production - Domain expertise in a specific enterprise vertical (recruiting, finance, ops, legal, etc.) - Familiarity with enterprise security requirements, VPC deployments, or on-prem configurations - History of building evals infrastructure or AI quality measurement tooling PERKS Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend 📚 Growth: $2,000 learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
AI Model Policy Trainer, Mental Health (Seattle)
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. Handshake AI works directly with frontier AI lab researchers to create evaluations, publish benchmarks, and improve AI models through human expertise. ROLE DETAILS Location: Onsite in Seattle, WA, Monday-Friday. Compensation: $45-$65/hr. Placement within the range depends on experience. Employer: TCWGlobal. This is a W-2 assignment supporting Handshake AI. Employment: Full time, 40 hours per week, non-exempt and eligible for overtime pay. Schedule: Monday-Friday, 8 a.m.-5 p.m. PT. ABOUT THE ROLE As an AI Model Policy Trainer focused on mental health, you will help evaluate how conversational AI systems respond to people discussing emotional distress, mental-health conditions, unusual beliefs, possible crises, and other sensitive experiences. You will review conversations and model behavior against a detailed mental-health safety policy. Your work will help determine whether an AI response is empathetic, appropriately grounded, and sensitive to risk without reinforcing unsupported or potentially harmful beliefs. This work requires an understanding of why people turn to AI for conversation, reflection, emotional support, or help during difficult moments. Strong candidates will recognize that AI can be useful and accessible while also understanding risks such as inappropriate validation, missed signs of crisis, overreliance, misleading guidance, or reinforcement of harmful beliefs. Direct experience supporting individuals or families through mental-health or behavioral-health challenges is required. This experience may come from clinical care, social work, nursing, crisis support, professional caregiving, certified peer support, family advocacy, care navigation, or another structured human-services setting. AI or technology experience is helpful, but it does not substitute for this domain experience. WHAT YOU WILL DO - Review user conversations and AI responses involving mental health, emotional distress, crisis, unusual beliefs, paranoia, hallucinations, mania, and related experiences - Apply detailed policy taxonomies and evaluation criteria to classify user requests and model behavior; evaluate individual messages and changes across longer conversations - Distinguish between validating a person’s emotions and validating an unsupported or potentially harmful explanation; assess whether responses reinforce or escalate harmful beliefs - Evaluate actions taken by AI systems through tools, including searches, messages, scheduling, purchases, file creation, and publication - Write clear rationales that connect each evaluation decision to evidence from the conversation and policy - Participate in calibration exercises and work with other trainers to improve consistency and provide evidence-based peer feedback - Identify ambiguous examples, gaps, and edge cases that may require policy clarification - Collaborate with researchers, policy specialists, operations teams, and other experts; incorporate coaching as policies and model capabilities evolve WHO MAY BE A GOOD FIT Qualified candidates must have direct experience in one or more of the following areas: - Mental health or behavioral health - Social work or community-based services - Nursing or patient care - Professional caregiving - Certified peer support - Family advocacy or care navigation - Crisis support or related human services Clinical licensure is valuable but is not required. Relevant professional caregiving, advocacy, certified peer-support, or other structured human-services experience may qualify. Interest or experience in AI is helpful, but it does not replace direct experience supporting people through mental-health or behavioral-health challenges. DESIRED CAPABILITIES - Required: direct experience supporting individuals or families through mental-health or behavioral-health challenges - Familiarity with conversational AI tools and an interest in how people use them for emotional support and a balanced understanding of their benefits and risks - Ability to interpret sensitive conversations with empathy, precision, and cultural awareness - Ability to follow detailed policies and distinguish between closely related categories - Strong written communication and the ability to explain decisions using specific evidence - Sound judgment when information is incomplete, ambiguous, or context-dependent - Openness to feedback, calibration, and evolving guidance, with constructive discussion of policy disagreements - Strong professional boundaries and comfort working independently with sensitive material EXTRA CREDIT - Experience with structured review, case documentation, assessment, triage, quality assurance, or rubric-based evaluation - Experience working with people experiencing crisis, psychosis, paranoia, mania, hallucinations, suicidal ideation, or severe emotional distress - Experience as a certified peer specialist, family advocate, patient advocate, case manager, crisis counselor, social worker, nurse, caregiver, or behavioral-health professional - Familiarity with ChatGPT, Claude, Gemini, or other conversational AI systems - Experience evaluating AI outputs, annotating data, applying content policies, or conducting quality reviews - Understanding of how culture, language, disability, socioeconomic circumstances, and access to care can affect mental-health conversations - Experience participating in case consultation, supervision, audit, or calibration processes YOU WILL THRIVE HERE IF - You are curious about why people turn to AI for immediate, private, accessible emotional support - You can acknowledge the potential value of AI without overlooking its limitations or risks - You avoid diagnosing people from limited text and do not treat every mention of mental health as an emergency - You can separate empathy for a person from agreement with their interpretation of an experience - You rely on evidence and policy criteria rather than intuition alone - You can change your conclusion when new context or stronger evidence becomes available - You are comfortable discussing policy disagreements respectfully and applying the final guidance consistently - You care about building AI systems that respond to vulnerable people with greater safety, nuance, and humanity LOCATION REQUIREMENT This position is based in Seattle, Washington. Candidates must currently be located in the Seattle area or be willing to relocate to Seattle for the position. CONTENT WARNING This role involves regular and deliberate exposure to sensitive and potentially distressing material. You may review content involving suicide, self-harm, psychosis, paranoia, hallucinations, mania, abuse, violence, substance use, severe emotional distress, and other mental-health or crisis-related situations. Candidates must be able to engage with this material professionally and sustainably. Support resources are available. BENEFITS Benefits are provided through TCWGlobal. Eligible employees can enroll in medical coverage, including prescription and mental health benefits, dental and vision insurance, healthcare and dependent care flexible spending accounts, and pretax commuter benefits. A 401(k) retirement plan with an employer match is available to eligible participants. Additional offerings include voluntary accident, critical illness, and term life insurance, wellness and pet-related reimbursements, charitable matching, and employee discounts. Eligibility requirements, waiting periods, employee contributions, and plan terms apply. Full-time employees scheduled for at least 30 hours per week are eligible for health coverage beginning the first of the month following at least 30 days of employment. Retirement plan eligibility follows a separate schedule. Paid time off: PTO accrues from the first day of the assignment at one hour per 40 hours worked, with no waiting period to use accrued PTO. PTO may be used for vacation, personal days, or illness, subject to policy approval requirements. Accrual is capped at 80 hours per year and balances at 100 hours, unless otherwise required by law. Additional paid sick leave is provided in accordance with applicable Washington and Seattle requirements. Paid holidays: The holiday policy lists 13 paid holidays. Eligible employees receive eight hours of holiday pay at their base hourly rate for observed holidays that fall on a scheduled workday, subject to the holiday policy. See the TCWGlobal 2026 Benefits Guide https://www.tcwglobal.com/benefitsguide-basic-2026 for coverage options, costs, and enrollment details. INTERVIEW PROCESS The process includes application review, a recruiter screen, a hiring manager screen, onsite interviews, and a final round before the offer stage. Your recruiter will share the next steps as you move through the process. EQUAL OPPORTUNITY AND ACCOMMODATIONS TCWGlobal is an equal opportunity employer. Hiring decisions are based on qualifications and abilities, without discrimination based on characteristics protected by applicable law. Reasonable accommodations are available during the application and interview process. If you need an accommodation, please let your recruiter know.
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