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Robot Science Ops
ABOUT GENERALIST At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done. We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world. The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, https://research.google/blog/palm-e-an-embodied-multimodal-language-model/ RT-2 https://deepmind.google/blog/rt-2-new-model-translates-vision-and-language-into-action/, Gemini Robotics https://deepmind.google/models/gemini-robotics/), launched and scaled ChatGPT https://chatgpt.com/ and GPT-4 https://openai.com/index/gpt-4-research/ to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas https://bostondynamics.com/atlas/, Spot https://bostondynamics.com/products/spot/, Stretch https://bostondynamics.com/products/stretch/) and pushed the limits of what they can do (from parkour https://www.youtube.com/watch?v=tF4DML7FIWk to manipulation https://bostondynamics.com/blog/large-behavior-models-atlas-find-new-footing/, and testing robustness https://www.youtube.com/watch?v=aFuA50H9uek). We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. ABOUT THE ROLE: This is a deeply cross-functional, execution-oriented ops role at the center of our model research and robotics stack. As a member of the Robot Science Operations staff, you will help turn robots, data, models, and evaluations into a tight, high-velocity feedback loop for model science. Foundation model intelligence is only as good as the evaluations we can hill climb on, and this role is responsible for making those evaluations real, reliable, and repeatable. You will execute experiments directed by our research teams on a variety of robot platforms. You will help design tasks, coordinate robot data collection, kick off training jobs, run evaluations, analyze results, and ensure robots are physically ready for rollouts. You may build physical benchmarks, lightly modify hardware setups, test third-party tooling, and write documentation that enables others to replicate and scale your work. YOU’LL BE RESPONSIBLE FOR: - Executing a range of experiments on our robot platforms - Collaborate closely with the research teams on results and be required to synthesize and interpret your findings - Designing new robotic tasks and benchmarks to evaluate model capabilities - Procuring materials and building lightweight physical benchmarks - Ensuring robots are properly configured, calibrated, and ready for rollouts and evaluations - Running structured evaluations and measuring real-world success rates - Analyzing results and closing feedback loops with ML researchers - Beta testing internal and third-party tools for teaching robots new skills - Writing clear documentation and playbooks so others can reproduce workflows - Identifying operational bottlenecks and improving system throughput end-to-end YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Be continuously diligent in the face of seemingly repetitive, but subtly changing task evaluations. - Have hands-on experience with robot data collection, evaluation, or deployment - Have conceptual understanding of the full modern ML training, fine-tuning, and inference life cycles - Are comfortable running experiments and tracking real-world metrics across multiple model variants - Enjoy operating across software, hardware, and physical systems - Have some exposure to basic EE/ME tasks (wiring, mounting sensors, assembling fixtures, debugging hardware) - Are highly organized and can coordinate multiple moving parts simultaneously - Write clear, structured documentation - Prefer execution and iteration speed over theoretical purity - Like being the person who “just makes it work” WHAT THIS ROLE IS NOT You will be a part of the ML team, and working very closely with ML, brainstorming ideas, and may prototype as well. However: - This is not a pure ML research role focused on designing new model architectures or advancing core learning algorithms. - This is not a large-scale infrastructure engineering role building distributed systems, databases, or UI platforms. - This is not a deep robotics controls or firmware engineering role. Instead, this role sits at the intersection of ML, robotics, and operations. You are ensuring our systems run end-to-end in the real world, and improving them through tight execution loops. If you are most excited by hands-on iteration, cross-functional execution, and accelerating the entire system this role may be a strong fit.
Senior Software Engineer, Inference Engine (Platfo...
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon. Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise. About the Role Software Engineer (Inference Engine) is responsible for developing and optimizing a high-performance inference engine for Large Language Models (LLMs) and multimodal LLMs running on FuriosaAI NPUs. In this role, you will proactively research and apply the state-of-the-art inference optimization techniques to our inference engine. You will work in close collaboration with the compiler and hardware teams to enhance the engine's performance to its full potential. Key Responsibilities - Design and implement FuriosaAI’s next-generation inference engine for large and multimodal language models—comparable in capability to frameworks such as vLLM and SGLang—optimized for throughput, latency, and memory efficiency. - Design and implement advanced inference optimizations—such as speculative decoding, KV-cache management, tensor/model parallelism, memory-efficient execution, and scheduling—in our production inference engine. - Design and develop capabilities for distributed and scalable inference, including prefill–decode (PD) and encode–prefill–decode (EPD) disaggregation, disaggregated speculative decoding, and hierarchical and external KV-cache storage such as HiCache and Mooncake. - Collaborate closely with the Compiler team to co-design and optimize execution for FuriosaAI NPUs, improving system-level throughput, latency, and memory utilization. - Proactively research, evaluate, and integrate state-of-the-art inference optimization techniques and key features of LLM serving frameworks into our production inference engine. Minimum Qualifications - BS degree in Computer Science, Engineering, or a related field, with at least 3 years of relevant industry experience, or equivalent practical experience - Proficiency in Rust or C++ programming skill - Knowledge and passion of deep learning, LLM, and/or generative AI models - Excellent problem-solving and data analysis skills. - Strong communication and collaboration skills. Preferred Qualifications - Experience in building inference serving systems for large models, encompassing batching, scheduling, caching, and load balancing. - A deep understanding of performance optimization systems. - Proficiency in C++/CUDA or Triton kernel development - Contributions to open-source inference frameworks such as vLLM, SGLang, or TensorRT-LLM. Why Join FuriosaAI The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up. With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion. At Furiosa, you will: Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI. Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks. Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS. Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC. Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition. Contact - recruit@furiosa.ai
Strategic Pursuits Account Executive, AI Native
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. ABOUT THE ROLE We’re hiring an Strategic Pursuits Account Executive, AI Native to drive adoption of Fireworks within the most ambitious and strategic AI companies. This isn’t a traditional sales role: we’re looking for someone who can speak credibly to technical teams, identify high-impact use cases, and relentlessly pursue value creation for the customer. We are looking for highly motivated, networked, and technically adept individuals to serve as trusted advisors to our most important customers and prospects. You’ll engage deeply with technical founders, ML leads, and product teams, helping them understand how Fireworks fits into their stack and guiding them through evaluation, onboarding, and scale-up. You’ll work in lockstep with our Applied AI team on key accounts, partner with product and ML specialists to architect the right technical approach, and run a clean commercial cycle with our GTM partners. You’ll be the quarterback of the account from initial POC through production at scale. RESPONSIBILITIES Technical Partnership & Execution - Lead technical and product discovery and conversations with founders, ML engineers, and infra leads. - Work closely with Field Engineering, Applied AI, Product and Research teams to shape tailored solutions, POCs, and fine-tuning approaches. - Translate customer feedback into actionable insights for Fireworks product and engineering with specificity and urgency. - Help customers get live quickly by coordinating onboarding, benchmarking, and integration efforts. Deal Management & Commercial Execution - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria before proposing solutions. - Manage multiple concurrent accounts with fast iteration cycles. Prioritize ruthlessly, keep scope tight, and maintain momentum. - Structure and negotiate complex commercial terms. - Actively identify, engage, and qualify new prospects through executive and investor networks, industry events, and partnerships. - Run a disciplined operating cadence with your portfolio of customers: reviewing key trends, driving outcomes, and jointly planning the next phase of the partnership. Executive Alignment and Ecosystem Presence - Own the relationship with key Strategic AI Native accounts, from first engagement through production deployment. Earn trust with ML engineers and Founders in the same meeting. - Nurture and shape strong executive relationships. - Be a visible representative of Fireworks in the AI startup ecosystem. YOU MIGHT BE A FIT IF YOU - Have 7+ years of experience as a PM, strategic account executive, VC,, or previous management consulting experience focused on serving highly technical buyers and portfolio companies - Demonstrated ability to run multi-threaded customer engagements: mapping stakeholders, managing commercial cycles, and maintaining deal and relationship momentum - Technical fluency to lead discovery with ML engineers and infrastructure leads and ability to discuss open-source vs. proprietary models, model tuning, reserved capacity, and compliance requirements - Thrive in fast-moving environments and love engaging with leading startup founders and builders - Are proactive, persistent, and creative in breaking into accounts and building lasting relationships throughout the organization - Have strong communication skills and can earn trust with both engineers and executives - Want to be on the front lines of the AI movement and work closely with companies shaping the future WHY FIREWORKS - Help define AI Native Strategic Pursuits go-to-market for one of the fastest-growing AI infrastructure companies in the world - Work directly with the most innovative AI startups - Join a lean, high-impact GTM team where your work drives outsized influence on company trajectory - Build lasting relationships and help startups get real value from best-in-class infrastructure - Collaborate with world class engineers and operators building at the bleeding edge of AI - Competitive salary, equity in a fast-growing startup, comprehensive benefits package, and long-term upside Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted. OTE Pay Range (Plus Equity) $300,000-$340,000 USD; 50/50 split + Stock Options Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Senior Sales Manager, AI Native
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. ABOUT THE ROLE We're looking for an Senior Sales Manager, AI Native to build, coach, and scale the team selling into the most ambitious GenAI-native companies in the world. This person will lead a team of AI Native Account Executives, own new business and expansion across a portfolio of GenAI startups, and build the repeatable playbooks that turn early technical traction into production-scale revenue. Fireworks is past $1B ARR and trusted by GenAI-native companies like Cursor, Vercel, and Genspark. The AI Native segment moves faster than any other part of our business — founders evaluate in days, workloads scale in weeks, and the buyer is almost always technical. This is a hands-on leadership role for someone who can both set strategy and get in the deal. You'll be expected to raise the bar on technical credibility, discovery rigor, usage growth, and forecast accuracy, while creating an environment where AEs learn quickly and grow into future GTM leaders. WHAT YOU’LL DO - Lead, coach, and develop a team of AI Native Account Executives selling into GenAI-native startups. - Own team performance against new logo, consumption growth, pipeline, and forecast accuracy goals. - Build and refine the AI Native sales motion - from first technical conversation through evaluation, benchmarking, POC, and production scale. - Coach AEs to lead credible technical conversations with founders, ML engineers, and infra leads, and to earn trust with both engineers and founders. - Partner with GTM engineering, product, and applied AI to unblock adoption, shape tailored solutions, and accelerate time to value in your team's accounts. - Partner with Sales Development, Marketing, and RevOps on target accounts, territories, qualification standards, inbound routing, and funnel conversion. - Establish clear operating rhythms, including pipeline reviews, deal reviews, call reviews, coaching sessions, and weekly forecast inspection. - Use usage and account health data to identify expansion opportunities, diagnose churn or stalled adoption, and prioritize the highest-impact accounts. - Translate patterns across the segment into actionable product and roadmap feedback. - Hire, onboard, and ramp new AEs as the team scales. - Represent Fireworks in the GenAI ecosystem - demo days, meetups, and online communities - and build the team's presence there. - Create a culture of accountability, curiosity, technical depth, and continuous improvement. WHAT WE’RE LOOKING FOR - 5+ years of experience in sales or business development selling to technical buyers, with experience managing or formally coaching quota-carrying AEs. - Proven ability to win and grow accounts in a technical, infrastructure, AI, or developer-oriented market - especially consumption or usage-based models. - Strong coaching skills, especially around technical discovery, multi-threading, POC and evaluation management, negotiation, and executive communication. - Comfort operating in an early-stage or high-growth environment where playbooks are still being built. - Ability to understand and explain technical topics like open-source inference, API performance, model tuning, or GPU architecture - and to hold your own with a founder or ML lead. - Strong analytical orientation and ability to use pipeline and consumption metrics to diagnose performance and improve team execution. - Excellent written and verbal communication skills. - High standards for talent, process, and operational rigor. - Ability to partner cross-functionally with Product, Engineering, Applied ML, Marketing, RevOps, and Recruiting. - Genuine enthusiasm for working with startup founders and builders on the front lines of the GenAI movement. NICE TO HAVE - Experience selling into engineering leaders, product leaders, founders, or AI/ML teams. - Experience supporting AI-native, developer-tooling, data infrastructure, cloud, or open-source GTM motions. - Prior experience building a sales team or segment from an early stage. - Background in a technical or product role before moving into sales leadership. - - Familiarity with tools such as Salesforce, Gong, Lemlist, LinkedIn Sales Navigator, Clay, or similar revenue platforms. WHAT SUCCESS LOOKS LIKE - The team consistently lands and grows GenAI-native accounts aligned to Fireworks' priority segments. - AEs are technically credible, run rigorous evaluations and POCs, and shorten time from first conversation to production workload. - Consumption in existing accounts grows predictably, with expansion identified from usage data rather than guesswork. - Forecasts are accurate, pipeline is well-inspected, and the operating rhythm is clear to everyone on the team. - New AEs ramp quickly and understand both the technical context and commercial value of Fireworks. - Feedback from the segment reliably reaches product and engineering and shapes what we build. LOCATION San Mateo, CA / San Francisco, CA WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Member of Technical Staff, Performance Optimizatio...
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE: We're looking for a Software Engineer focused on Performance Optimization to help push the boundaries of speed and efficiency across our AI infrastructure. In this role, you'll take ownership of optimizing performance at every layer of the stack—from low-level GPU kernels to large-scale distributed systems. A key focus will be maximizing the performance of our most demanding workloads, including large language models (LLMs), vision-language models (VLMs), and next-generation video models. You’ll work closely with teams across research, infrastructure, and systems to identify performance bottlenecks, implement cutting-edge optimizations, and scale our AI systems to meet the demands of real-world production use cases. Your work will directly impact the speed, scalability, and cost-effectiveness of some of the most advanced generative AI models in the world. KEY RESPONSIBILITIES: - Optimize system and GPU performance for high-throughput AI workloads across training and inference - Analyze and improve latency, throughput, memory usage, and compute efficiency - Profile system performance to detect and resolve GPU- and kernel-level bottlenecks - Implement low-level optimizations using CUDA, Triton, and other performance tooling - Drive improvements in execution speed and resource utilization for large-scale model workloads (LLMs, VLMs, and video models) - Collaborate with ML researchers to co-design and tune model architectures for hardware efficiency - Improve support for mixed precision, quantization, and model graph optimization - Build and maintain performance benchmarking and monitoring infrastructure - Scale inference and training systems across multi-GPU, multi-node environments - Evaluate and integrate optimizations for emerging hardware accelerators and specialized runtimes MINIMUM QUALIFICATIONS: - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience - 5+ years of experience working on performance optimization or high-performance computing systems - Proficiency in CUDA or ROCm and experience with GPU profiling tools (e.g., Nsight, nvprof, CUPTI) - Familiarity with PyTorch and performance-critical model execution - Experience with distributed system debugging and optimization in multi-GPU environments - Deep understanding of GPU architecture, parallel programming models, and compute kernels PREFERRED QUALIFICATIONS: - Master’s or PhD in Computer Science, Electrical Engineering, or a related field - Experience optimizing large models for training and inference (LLMs, VLMs, or video models) - Knowledge of compiler stacks or ML compilers (e.g., torch.compile, Triton, XLA) - Contributions to open-source ML or HPC infrastructure - Familiarity with cloud-scale AI infrastructure and orchestration tools (e.g., Kubernetes) - Background in ML systems engineering or hardware-aware model design EXAMPLE PROJECTS: - Implement fully asynchronous low-latency sampling for large language models integrated with structured outputs - Implement GPU kernels for the new low-precision scheme and run experiments to find optimal speed-quality tradeoff - Build a distributed router with a custom load-balancing algorithm to optimize LLM cache efficiency - Define metrics and build harness for finding optimal performance configuration (e.g. sharding, precision) for a given class of model - Determine and implement in PyTorch an optimal sharding scheme for a novel attention variant - Optimize communication patterns in RDMA networks (Infiniband, RoCE) - Debug numerical instabilities for a given model for a small portion of requests when deployed at scale WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Member of Technical Staff, Cloud Infrastructure
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE: As a Software Engineer on our Cloud Infrastructure team, you'll be at the forefront, architecting and building the foundational systems that power Fireworks AI's revolutionary generative AI platform. You'll spearhead the creation of one of the world's first virtual clouds, seamlessly serving AI workloads across the globe and every cloud provider. Your mission: to deliver unparalleled reliability, efficiency, and scalability, fueling the world's most innovative AI products.This is a highly technical role requiring deep expertise in distributed systems, cloud-native infrastructure, and machine learning platforms. You’ll partner closely with engineering partners, product teams, and infrastructure stakeholders to design solutions that balance performance, cost-efficiency, and operational simplicity across compute, storage, and networking layers. KEY RESPONSIBILITIES: - Architect and build scalable, resilient, and high-performance backend infrastructure to support distributed training, inference, and data processing pipelines. - Lead technical design discussions, mentor other engineers, and establish best practices for building and operating large-scale ML infrastructure. - Design and implement core backend services (e.g., job schedulers, resource managers, autoscalers, model serving layers) with a focus on efficiency and low latency. - Drive infrastructure optimization initiatives, including compute cost reduction, storage lifecycle management, and network performance tuning. - Collaborate cross-functionally with ML, DevOps, and product teams to translate research and product needs into robust infrastructure solutions. - Continuously evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Kubeflow, MLFlow) to enhance our platform’s capabilities and reliability. - Own end-to-end systems from design to deployment and observability, with a strong emphasis on reliability, fault tolerance, and operational excellence. - Ensuring System Reliability: Ensure systems are designed and implemented with high availability, scalability, and performance. Focus on fault tolerance, disaster recovery, identifying and removing scaling bottlenecks, and performance optimization across our multi-cloud infrastructure. - Observability & Monitoring: Develop, implement, and maintain comprehensive monitoring, alerting, logging, and tracing solutions to provide deep insights into system health and performance MINIMUM QUALIFICATIONS: - Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience). - 5+ years of experience designing and building backend infrastructure in cloud environments (e.g., AWS, GCP, Azure). - Proven experience in ML infrastructure and tooling (e.g., PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes, etc.). - Strong software development skills in languages like Python, or C++. - Deep understanding of distributed systems fundamentals: scheduling, orchestration, storage, networking, and compute optimization. PREFERRED QUALIFICATIONS: - Master’s or PhD in Computer Science or related field. - Experience leading infrastructure projects supporting large-scale ML/AI workloads or high-throughput systems. - Familiarity with infrastructure-as-code and CI/CD tooling (e.g., Terraform, ArgoCD, GitOps). - Track record of driving system performance, reliability, and cost-efficiency improvements. - Contributions to open-source cloud or ML infrastructure projects a plus. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Member of Technical Staff- Full Stack
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE We are looking for a Full Stack Software Engineering to architect, build, and scale our developer-focused web application (fireworks.ai) and shape our end-to-end technical architecture. This role blends hands-on engineering with technical leadership, offering the opportunity to mentor other engineers, collaborate cross-functionally, and drive innovation in a fast-paced, AI-focused environment. You'll play a key role in delivering scalable, elegant, and highly performant solutions that directly impact our hundreds of thousands of developers and product vision. You will be directly shaping and shipping the most optimal developer journey—spanning intuitive front-end interfaces, robust APIs, and efficient backend orchestration—combined with our large offering of open-source generative AI models, enabling our users to seamlessly build, experiment, and ship their AI workflows with our playground. KEY RESPONSIBILITIES - End-to-End Ownership: Engineering ownership of fireworks.ai from the user interface down to the API and data layer, with a strong focus on a delightful developer journey. - Product-Led Growth: Participate in the team’s shared accountability for product-led growth through the web application, model playground, and seamless user onboarding workflows. - Full Stack Development: Design, develop, and test responsive, performant web applications alongside robust, scalable backend services and APIs. - Leadership & Mentorship: Mentor and support a team of full stack, frontend, and backend engineers through code reviews, pair programming, and ongoing technical coaching. - Architectural Excellence: Define and implement full stack architectural standards, API design best practices, database schemas, and modern development workflows. - Cross-Functional Collaboration: Partner with Product, Design, and Core AI/Infrastructure Engineering to align on requirements, system design, timelines, and delivery expectations. - Systems & Components: Build and maintain reusable, scalable frontend component libraries while ensuring backend services are modular and easily integrated. - Unified Developer Experience: Partner with other engineering teams to build an aligned developer journey across web, SDK, and CLI surfaces. - Quality & Performance: Champion application performance, security, data integrity, and accessibility across the entire software stack. - Innovation: Drive innovation by staying informed of emerging full stack trends, cloud-native technologies, and AI orchestration frameworks. MINIMUM QUALIFICATIONS - Education: Bachelor’s degree in Computer Science or a related field, or equivalent practical experience. - Experience: 6+ years of professional experience in full stack software development. - Leadership: 2+ years of experience in a technical leadership role (e.g., tech lead, team lead, or engineering manager). - Frontend Proficiency: Strong expertise in React, TypeScript, JavaScript, and Next.js. - Backend Proficiency: Strong expertise in building server-side applications, designing RESTful or GraphQL APIs, and working with modern backend languages (e.g., Node.js, Python, Go). - Data Management: Solid understanding of database systems (SQL/NoSQL), caching strategies, and data modeling. - Track Record: Proven track record of delivering and scaling production-grade, full stack web applications. - Architecture & Devops: Experience with modern cloud infrastructure (AWS, GCP, or OCI), containerization (Docker), and full stack CI/CD pipelines. PREFERRED QUALIFICATIONS - AI/ML Domain Knowledge: Experience working in AI/ML-focused environments, or interacting with LLM APIs, vector databases, and model orchestration tools (e.g., LangChain, LlamaIndex). - Startup Agility: Prior startup experience—especially as a technical founder or early engineer—is a major plus. - People Growth: Experience managing or mentoring other engineers, including providing performance feedback and supporting career development. - Developer Tooling: Prior experience building developer platforms, SaaS dashboards, or complex interactive environments like playgrounds and sandboxes. - Open Source: Contributions to open-source projects, internal component libraries, or developer tools. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Member of Technical Staff (EMEA)
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE: As a Member of Technical Staff on the EMEA field team, you build on top of one of the largest inference platforms in the world. The work spans the stack: capabilities on top of inference and serving, tooling around fine-tuning and post-training of LLMs, and the product our region’s customers need that the core platform team will not take on. You are first and foremost an excellent software engineer; that is what we are testing for. You prefer building product to being customer-facing, and that is exactly right for this role, though you are welcome to join customer work when it interests you. Treat this as a flexible role: a bucket for exceptional builders at different levels of experience rather than a fixed job spec. There is no specific seniority requirement; anywhere from 3 to 10 years of experience can fit. What we value most is first principles thinking: reasoning about unfamiliar problems from the ground up rather than from playbooks. You will be evaluated on this directly in the interview process, and strength here can outweigh gaps elsewhere in your background. KEY RESPONSIBILITIES: - Build: Design and ship product capabilities end to end, from ambiguous need to running in production. - Build on Inference: Create capabilities on top of the serving stack: routing, model controls, observability, and whatever a deployment turns out to need. - Build on Training: Ship tooling around fine-tuning and post-training of LLMs, from data pipelines to evaluation, working alongside our applied ML engineers. - Own Regional Capability: Turn EMEA-specific requirements into product, working with core platform where the line is unclear. - Engineering Quality: Set the engineering bar for the regional team; your code is the reference. - Agentic Development: Use coding agents and AI tooling as a core part of how you build, with judgment about when to trust the output. - Optional Customer Work: Join deployments or customer conversations when useful or interesting; never required. MINIMUM QUALIFICATIONS: - First principles and critical thinking: the ability to break down novel problems and reason to a solution without a reference implementation. This is the primary interview signal and can outweigh other qualifications. - Excellent software engineering: depth in backend systems and infrastructure, and a track record of shipping production systems you owned. - Strong coding skills in Python and at least one systems language. - Fluent in AI-assisted and agentic engineering: uses coding agents and AI tooling as a core part of how you build, and knows when to trust the output and when not to. - Genuine interest in inference and AI infrastructure. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Member of Technical Staff - AI Infrastructure Reli...
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. About the Role Fireworks AI is one of the industry leaders in inference and training for open models. Open models are how the rest of the world gets to build on frontier AI without handing the keys to a single vendor, and our job is to make them fast, cheap, and dependable enough that this is a real choice. That work is systems work: GPU scheduling, kernel and runtime performance, networking, storage, Linux. We serve over 40 trillion tokens a day doing it. Reliability Engineering makes sure that platform runs dependably as it grows. You will work across cloud infrastructure, AI systems, and product teams to make sure the pieces fit together, fail gracefully, and hold up under load. How We Think About Ownership - You own the bar. You define what "reliable" means at Fireworks: SLOs, error budgets, production readiness, on-call expectations. Then you drive adoption across engineering. - You own the process and the tooling. Incident management, postmortems, observability standards, failure testing, guardrails, and automation are yours end to end. - Every team owns the reliability of what they build. You make that ownership practical. Structured logging and aggregation, metrics and tracing that work the same way everywhere, alerting that routes to the right owner, dashboards that answer "why is this slow." - You choose where the leverage is. You have a wide view of the platform and the latitude to spend your time where it changes outcomes most. Responsibilities - Define reliability standards: SLOs, error budgets, production readiness criteria. Not written in a vacuum: you instrument the systems and read the real telemetry the numbers come from. - Own the reliability toolchain: Logging and telemetry pipelines, alerting standards, failure injection, load testing, self-healing automation, and AI-assisted investigation tooling. - Keep customer experience from falling through the cracks: Per-service reliability is necessary but not sufficient. A customer can hit a bad experience while every system sits inside its SLO. You make sure those failures get an owner and a fix. - Own the seams: The hardest failures live between systems: retries that amplify load, timeouts that do not compose, dependencies nobody mapped. You find them before customers do and drive fixes through the teams that own them. - Run incident management: Coordinate live production issues, run blameless postmortems, and track follow-ups to completion. - Reduce toil: Automate repetitive operational work so growth does not turn into an unsustainable on-call load. - Partner across the org: Cloud infrastructure on capacity and multi-region risk, inference and training on failure modes in the serving and training stacks, performance on zero-downtime rollouts, product and control plane on customer-facing reliability. Qualifications - Systems fundamentals: 5+ years with Linux internals, system performance troubleshooting, and networking fundamentals (TCP/IP, HTTP, gRPC). - Software engineering: 5+ years in Python, Go, C++, or Rust, writing production-grade tools and systems code. - Cloud-native operations: Operating and debugging Kubernetes, Terraform, and Docker in high-throughput production. - Distributed systems: High-throughput control planes, microservices, or multi-region setups. - Reliability fundamentals: Fault-tolerant design, SLO/SLA management, automated failover, high-availability architecture. - Influence without authority: You can get other teams to adopt a standard through credibility and useful tooling rather than mandate. - Breadth over comfort: Willingness to dig into unfamiliar parts of the stack when a problem crosses boundaries. - Education: Bachelor's or Master's in Computer Science, Computer Engineering, or equivalent practical experience. Preferred Qualifications - Observability tooling: Prometheus, Grafana, OpenTelemetry, and alerting people actually act on. - GPU and ML infrastructure exposure: GPUs, inference serving, or distributed training. - AI-assisted operations: Building agents or LLM-based tooling for investigation, triage, or automation. - Open source background: Contributions to infrastructure, systems, or ML serving projects. - Startup agility: Comfortable where pragmatism and teamwork matter more than process. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
AI Product Engineer - Nexus
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. ABOUT THE ROLE We just shipped Fireworks Nexus: a drop-in platform that lets engineering organizations route their AI workloads off expensive proprietary models and onto high-performing open models like Kimi-K3 and GLM-5.2, without changing how a single developer works. The early numbers are the kind that change how an industry buys intelligence: 3–5x lower AI spend, roughly a third off the cost of every merged PR, and a blended token rate about a quarter of the closed labs, all while matching or beating frontier models on real engineering work from real customer repositories. The context is simple. AI spend at serious engineering orgs is exploding, one company burned its entire annual AI budget in four months, and most of that money goes to running routine work at frontier prices. Open models just crossed the intelligence-cost curve. Nexus is how teams capture that, and we're building it in the open: FireConnect ships under Apache 2.0, installs in one line, and plugs straight into Claude Code, Codex, and OpenCode. We're looking for a product-minded engineer to join as a Member of Technical Staff and own the surfaces that make this real: the intelligent router that scores and directs every request, the cost-observability and enterprise-control layers that give an org visibility over its entire AI footprint, the FireConnect integrations that make adoption a single command, and the core platform underneath; inference APIs, the developer console, and fine-tuning workflows. This is a high-autonomy IC role on a small team building something that ships to production the day you write it, at a scale almost nowhere else can offer. You'll own features end to end — from understanding the problem, to designing the solution, to shipping it, to watching how developers actually use it. If you're the kind of engineer who ships things other people think are impossible, on timelines other people think are impossible, this is a place where that has enormous leverage and nothing standing between you and impact. WHAT YOU'LL DO - Own product features end-to-end across Nexus and the broader Fireworks platform, the intelligent router, FireConnect harness integrations, cost observability, enterprise controls and policy, the developer console, API surfaces, the model playground, fine-tuning workflows, and billing, scoping the problem, building it, shipping it, instrumenting it, and iterating on real usage. - Build the routing and migration layer that scores request difficulty in real time and sends routine work to open models while passing hard tasks through to a customer's existing provider, the system that delivers 3–5x cost reductions without sacrificing quality. - Make adoption frictionless: extend FireConnect and our Anthropic- and OpenAI-compatible APIs so a team can drop Nexus into their existing tools with just a base URL and a model ID, and improve the caching and infra paths that turn that into material cost savings. - Work across the full stack, frontend (React/TypeScript), backend services (Python, Go), APIs, and data layers, to ship polished, production-quality product surfaces for deeply technical users. - Build for products evolving week to week: new models, new serving paths, new consumption models, new enterprise controls, and new multi-agent harness tooling. - Partner closely with Infrastructure, Applied Research, Growth, Data, and Design to turn raw platform capability into products developers love. - Instrument everything you build and let the data tell you where the friction is — then remove it. MINIMUM QUALIFICATIONS - 3+ years as a software engineer, with meaningful time spent building and shipping user-facing products. - Strong full-stack skills, comfortable across frontend (React/TypeScript), backend (Python, Go, or similar), APIs, and databases. - A track record of shipping developer-facing products: APIs, dashboards, consoles, CLIs, or developer tools. - Genuine end-to-end ownership, you're as comfortable scoping an ambiguous problem as you are deploying the fix at 2am. - Strong product instincts: you optimize for the developer experience, not just the diff. - The ability to operate at high velocity with extreme ownership: you ship fast, make pragmatic trade-offs, and don't wait to be told what to build. PREFERRED QUALIFICATIONS - Experience building products on top of complex infrastructure, inference platforms, cloud services, data platforms, or ML tooling. - Experience building for deeply technical users, where the product surface is an API as much as a UI. - Comfort in a fast-moving, founder-led environment where the product changes week to week and you're drawing the map as you walk it. - You build with AI tools every day, and you have sharp intuition for what a great AI developer experience feels like from the inside. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Senior Software Engineer, MLOps
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. We are seeking a skilled and motivated Senior MLOps Engineer to join our engineering team. In this role, you will design and maintain the infrastructure and tooling that supports the full lifecycle of machine learning systems used in robotics applications. You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an exciting opportunity to help operationalize machine learning in real-world robotic systems within a fast-growing and dynamic environment. What You Will Get To Do Design, build, and maintain GPU based infrastructure for machine learning pipelines, including data processing, training, evaluation, inference and deployment workflows. Collaborate closely with robotics teams to implement model serving infrastructure for edge/robot deployment. Build tools and automation to support reproducible experiments, model versioning, and dataset management. Deploy and manage ML services and inference pipelines using containerized environments for efficient scaling and scheduling of heterogeneous compute resources. Monitor model performance and system reliability across development and production environments. Improve the efficiency, scalability, and reliability of ML workflows and infrastructure. Work with cross-functional engineering teams to integrate ML components into robotics software systems. What You Have Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent work experience). 3-7 years of experience in MLOps, machine learning infrastructure, or related engineering roles. Strong programming skills in Python or similar languages. Experience building and maintaining machine learning pipelines. Hands-on experience with cloud and cloud-native tools such as AWS (SageMaker, S3, or similar cloud ML services), Kubernetes etc., Solid understanding of Linux systems and distributed computing environments. Experience with GPU workload scheduling and orchestration across multi-region cloud environments. Excellent problem-solving skills and the ability to work collaboratively in a team environment. What Will Set You Apart Experience deploying and operating ML systems for robotics or real-world physical systems. Experience with scaling AI, ML, and inference workloads on Kubernetes. Exposure to ROS-based robotics data formats and pipelines (rosbags, point clouds) Experience with experiment tracking, model versioning, or dataset versioning tools. Experience optimizing ML pipelines for large-scale training and data processing. Experience working closely with research or applied machine learning teams.
Senior ML Engineer, Data Flywheel
FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. About This Role Modern ML systems improve through their data flywheel: production experience generates new data, that data is processed and understood, valuable examples are identified and labeled, datasets are created, models are retrained and evaluated, and the resulting models return to production. We are looking for an ML Engineer focused on the Data Flywheel to help build and automate this lifecycle for autonomous robots operating in complex real-world environments. This role sits between ML engineering and data engineering. You will work closely with perception/autonomy researchers, labeling, Data Platform, and ML Platform engineers to turn large volumes of robot experience into high-quality training data. What You'll Get to Do Build and maintain pipelines that transform robot data into training-ready ML datasets. Automate data processing, filtering, selection, transformation, labeling, and dataset-generation workflows. Develop scalable batch and offline inference pipelines for auto-labeling and data mining. Build systems for selecting useful or difficult examples from large volumes of robot data. Integrate manual labeling and model-assisted/automated labeling into repeatable data workflows. Implement data-quality checks and dataset validation. Build reproducible and versioned dataset-generation pipelines. Improve incremental dataset generation so new robot experience can efficiently feed future training cycles. Partner with researchers to translate experimental data-processing logic into reliable production pipelines. Measure and improve the efficiency of the loop from new robot experience to usable training data. What We're Looking For Strong Python and software engineering skills. Experience building ML/data-processing pipelines. Understanding of ML dataset construction and training workflows. Experience processing large datasets using distributed or parallel computing. Experience with object storage, Parquet or similar formats, workflow systems, and cloud compute. Ability to bridge exploratory ML code and reliable production systems. Strong understanding of data quality and reproducibility. Nice to Have Computer vision, perception, robotics, or multimodal ML experience. Experience with auto-labeling, active learning, hard-example mining, or data selection. Experience processing images, video, point clouds, LiDAR, or other sensor data. Ray/Spark or similar distributed-processing experience.
Robotics Autonomy Engineer, Manipulation
FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. About the Job Field AI is building the future of autonomy—from rugged terrain to real-world deployment. We’re on a mission to develop intelligent, adaptable robotic systems that operate beyond simulation and thrive in unpredictable environments. As our Robotics Autonomy Engineer – Manipulation, you’ll lead the development and deployment of whole-body control and manipulation capabilities for humanoids and arm-equipped quadrupeds, turning real field scenarios into behaviors our robots perform reliably every day. You’ll be part of a deeply technical team advancing real-world robotic capabilities through cutting-edge research, simulation tools, and field validation. If building robots that can use their hands in the real world excites you, and you want to work where your code hits the ground (literally)—this is your role. This is Field AI. What You’ll Get To Do Develop whole-body control and manipulation capabilities for humanoids and quadrupeds with arms, coordinating base, torso, and arm motion as a single system Take specific field scenarios from concept to repeatable execution on hardware, interacting with the built environment and handling objects and tools Build learning based and model based manipulation policies and integrate them tightly with perception and locomotion Train manipulation policies from demonstration data and adapt vision language action (VLA) foundation models to our robots and tasks, then make them work on hardware Design grasp, contact, and force interaction strategies that hold up across varied objects, surfaces, and environments, with interaction forces kept safe for people and equipment nearby Harden behaviors so they succeed across repeated runs, changing lighting, object variation, and real site conditions Build simulation environments and evaluation pipelines for manipulation, and use field data to close the gap between simulation and the real world Deploy on physical robots and iterate rapidly through lab testing and field validation Work closely with locomotion, perception, and systems engineers to deliver end to end capabilities What You Have Master’s degree or higher in Robotics, Computer Science, Engineering, or related field (PhD strongly preferred) Deep expertise in robot manipulation or whole-body control 2+ years of experience developing and deploying manipulation behaviors on real robotic systems (preferred) Hands-on experience with robot arms, hands or grippers, and humanoid or mobile manipulation platforms Solid understanding of kinematics, dynamics, contact modeling, and force control Experience with manipulation planning and control, such as trajectory optimization or model predictive control (MPC) Experience with learning based manipulation, such as imitation learning, reinforcement learning (RL), or vision language action models Proficiency with simulation tools such as Isaac Lab, MuJoCo, or Drake Experience integrating perception for manipulation Strong Python and/or C++ development skills in Linux-based development environments Familiarity with machine learning frameworks (PyTorch, JAX, TensorFlow) A passion for building things that move in the real world The Extras That Set You Apart 3+ years of experience in an industry or startup robotics setting Experience with loco-manipulation on legged platforms or whole-body model predictive control for humanoids Experience fine tuning or deploying vision language action models on real robots Experience building teleoperation and demonstration data collection pipelines at scale Experience with cross embodiment or generalist manipulation policies that transfer across robots and tasks Experience with dexterous multi fingered hands, or with tactile and force torque sensing in closed loop manipulation Experience optimizing and deploying learning based controllers on resource constrained robotic platforms (ONNX Runtime, NVIDIA TensorRT, real time onboard inference) Publications or open-source contributions in manipulation, whole-body control, or robot learning (e.g., CoRL, RSS, ICRA, IROS) Familiarity with ROS/ROS2 or custom middleware for real-time control Experience debugging sim-to-real issues at scale
Research Scientist - AI Safety
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE ROLE As a Research Scientist - AI Safety at Faculty, you will conduct original technical research in AI safety to build the foundation for safe, trustworthy AI deployment. Operating at the forefront of AI, you will design and execute impactful experiments, study model behaviour, and develop robust, reproducible tooling. Working alongside Senior and Lead Research Scientists, you will bridge scientific discovery with practical application, helping translate complex technical insights for external partners, frontier labs, and national security institutes. This is an incredible opportunity to hone your expertise, shape emerging safety standards, and solve some of the most critical challenges in modern AI. WHAT YOU'LL BE DOING: - Executing technical research in AI safety by designing and running experiments to study and steer model behaviour. - Applying white-box and black-box methodologies, focusing on interpretability, steering, and behavioural studies of transformer-based LLMs. - Developing high-quality, modular, and reproducible research code in Python using deep learning frameworks like PyTorch. - Building and maintaining research infrastructure and technical tooling to accelerate scientific discovery. - Documenting and communicating experimental findings through high-quality academic papers, technical reports, and presentations. - Collaborating with senior scientists to identify literature gaps, refine hypotheses, and identify research scope. - Translating complex technical insights for diverse audiences, including external frontier labs, government bodies, and safety institutes. WHO WE'RE LOOKING FOR: - Solid background in machine learning fundamentals and transformer architectures (specifically LLMs). - A practical understanding of white-box and black-box interpretability techniques, such as steering vectors or mechanistic interpretability. - Demonstrated capability to take structured technical problems and formulate hypotheses - Strong programming skills in Python and deep learning frameworks like PyTorch, with a track record of writing clean, modular research code, using Git for version control. - Excellent communication, enabling you to translate complex technical concepts and experimental results into clear reports and presentations. - Curiosity and analytical rigour, combined with exposure to core AI safety areas such as robustness, evaluations, or uncertainty calibration. OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Thermo ML Resident
Overview Extropic is looking for junior ML scientists to join our residency program on either a part-time or full-time basis. This is a flexible program that can be similar to an internship (minimum 3 months) but we give our residents far more autonomy than most internships. Our hardware massively accelerates certain kinds of probabilistic inference, and residents will help pioneer the science of training models in the thermodynamic paradigm. Responsibilities - Collaborate with senior researchers to derive the theory of new probabilistic models and their learning rules, including energy-based models and diffusion models - Scale up experimentation infrastructure and optimize over the design space of models - Implement, visualize, and evaluate new architectures, training algorithms, and benchmarks - Publish papers, contribute to open source, and communicate design insights to our hardware team Required Qualifications - Experience in scientific Python with JAX or similar deep learning framework (PyTorch, TensorFlow, or Keras) - Strong foundations in probability and linear algebra - Projects or papers demonstrating hands-on experience in applied machine learning and data science Preferred Qualifications - Familiarity with deep learning theory and literature, including theory of over-parameterization and scaling laws - Experience training energy-based models (EBMs) or diffusion models - Experience with graph neural networks (GNNs) or graph message passing algorithms - Experience with infrastructure for deep learning experimentation and training (Slurm, Ray, Kubernetes, Weights & Biases, etc.) - Strong theoretical background in information geometry - Strong grasp of computational Bayesian methods, including MCMC sampling methods and variational inference - Publications in top ML conferences (NeurIPS, ICML, ICLR, CVPR, etc.) Extropic is an equal opportunity employer This position will require access to information subject to control under U.S. export control laws and regulations, including the Export Administration Regulations (“EAR”). Please note that any offer for employment will be conditioned on authorization to receive controlled items.
AI Engineer
ABOUT ELICIT Elicit is an AI research assistant that uses language models to help researchers figure out what’s true and make better decisions, starting with common research tasks like literature review. What we're aiming for: 1. Elicit radically increases the amount of good reasoning in the world. - For experts, Elicit pushes the frontier forward. - For non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit. 2. Elicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes https://ought.org/updates/2022-04-06-process. This expands our collective understanding of safe AGI architectures. Visit our Twitter https://twitter.com/elicitorgto learn more about how Elicit is helping researchers and making progress on our mission. WHAT IS AN "AI ENGINEER"? AI engineering is a new category of technical work. Its emergence is linked to the increasing availability of powerful new artificial intelligence tools: notably generative machine learning systems like large language models. The term was suggested by swyx on the Latent Space podcast https://www.latent.space/p/ai-engineer and we've written about it on our blog before. Elicit predicted the rise of powerful ML systems even before GPT-1 was trained, and has the deepest experience of building trustworthy, capable, and transparent applications using these tools. If you're a software engineer who relishes the more difficult parts of backend code—like concurrency, fault-tolerance, and distributed systems—you could be a great AI engineer. WHY WE'RE HIRING FOR THIS ROLE Since launching the newest version of Elicit last fall, response has been strong. We introduced Elicit Plus, our monthly subscription plan, and added thousands of paying users in a matter of months as well as hundreds of thousands of new sign-ups. This has been energizing for our team, but we want to ship more useful functionality to our users even faster. We believe that building great AI-powered products requires excellence across multiple parts of the tech stack: from frontend UX to infrastructure. But one of the crux areas is certainly how we prompt, invoke, respond to, and manage the suite of different ML models required to make Elicit work. This is what an AI engineer will be responsible for at Elicit. [https://app.ashbyhq.com/api/images/user-content/797554ae-ec94-4cd4-8a92-0ca2488582e0/60f9d7b3-e345-4666-94c4-65a6900e4710/elicit-team-1.jpeg] OUR TECH STACK - Backend: Node and Python. - Frontend: Next.js and TypeScript (we expect you to be 80+% focussed on backend work, however). - We like static type checking in Python and TypeScript - All infrastructure runs in Kubernetes across a couple of clouds - We use GitHub for code reviews and CI AM I A GOOD FIT? Consider the questions: - What's the difference between anyio, trio, and asyncio? - What does the await keyword do in JavaScript? - What is a Kubernetes pod, and how is it different from a container? - How would you manage state when using an LLM to power a conversation? If you have a solid answer for these—without reference to documentation—then we should chat! WHAT YOU'LL OWN - Backend implementation of our "living document" - We believe that user interactions with language models should be much deeper than yet more chatbot interfaces. - We wrote about our living document https://blog.elicit.com/living-documents-ai-ux/ approach which is one way in which users can have much richer LLM-powered product experiences. - You would work on, curate, extend, and improve the backend part of that technology. This is fascinating and challenging distributed systems work. - Building Elicit into a product researchers can’t live without - We ship useful, exciting features out to users on a weekly basis. Your focus will be on the code which exists between the BFF endpoints and the ML models we use. - You will work on a mix of known features / fixes, prototypes to validate ideas, and exploratory projects in between. - Our team is small, so we expect you to appreciate the user needs underlying everything you work on. You should be comfortable making decisions and trade-offs that help us fulfill users’ needs best. - Keeping Elicit’s bar for quality high - You’ll balance shipping features in the short term with building extensible and maintainable systems. - You will be responsible for your features in production: they need to be scalable, resilient, and easy to operate. - You’ll contribute to discussions around system design, performance evaluation, and architecture. PROJECTS YOU'LL CONTRIBUTE TO You can view sample projects here. https://airtable.com/app9at9MxvT5VQbss/shrPavNcNjMClBMB2 WHAT YOU BRING TO THE ROLE - Strong technical aptitude that allows you to move comfortably around our back-end tech stack, with strong computer science fundamentals. - A genuine curiosity and enthusiasm for the capabilities of language models. - A defensive, fault-first mindset. - Above-average communication skills. Elicit is a small, highly-collaborative team, so you’ll frequently be tapped to communicate complex engineering topics with stakeholders across the company. - A sense of joy in what you do. One thing we love about our team at Elicit is that everybody’s a craftsperson who cares deeply about their field. YOUR FIRST WEEK - Start building foundational context - Get to know your team, our stack, and the product roadmap. - You’ll get to know our company documentation and other supporting resources like Supporting Process, not Outcomes https://www.lesswrong.com/posts/pYcFPMBtQveAjcSfH/supervise-process-not-outcomes. - Make your first contribution to Elicit - By the end of your first week, you’ll have completed your first Linear issue, have a PR merged into our monorepo, gained understanding of our CI/CD pipeline, and learned about our monitoring and logging tools. YOUR FIRST MONTH - You’ll complete your first multi-issue project - As you learn the ropes, you’re able to tackle more impactful projects, with input from domain experts where you need it. - You’re actively improving the team - You’ll have gotten into the swing of contributing to regular team meetings and hack days, and you’ve demoed something you’ve worked on during a team sync. - You’ve added some documentation, how-to guides, diagrams, or other resources meant to help us and new hires in the future. - You’ve suggested an improvement to our development process. YOUR FIRST QUARTER - You’re flying solo - With the context you’ve gained, you’re able to implement changes independently and you’re comfortable making big, impactful decisions in the course of your work. - You’ve developed an area of expertise - Our engineering team is just a few people, so each person quickly becomes a go-to resource in some area of the tech. Within your first quarter, we expect that there’s a part of Elicit you’ll become the domain expert for that others reach out to for support when working in this area. - You actively research and improve the product - By the end of your first quarter, you’ll have gotten to know Elicit and our users well. We expect that you’ll have thought about and scoped some user-facing improvements to the product as well as identified technical improvements to implement. LOCATION AND TRAVEL We have a great office in Oakland, CA, and we'd love to see you there if you're local. That said, we're just as happy for you to work remotely. We do get the whole team together for a quarterly retreat somewhere fun, because in-person time matters to us. BENEFITS AND PERKS In addition to working on important problems as part of a productive and positive team, we also offer great benefits (with some variation based on location): - Flexible work environment: work from our office in Oakland or remotely with time zone overlap (between GMT and GMT-8), as long as you can travel for in-person retreats and coworking events - Fully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your family - Flexible vacation policy, with a minimum recommendation of 20 days/year + company holidays - Every Elician receives a $200 monthly wellbeing stipend to spend on whatever supports your health and wellbeing. - 401K with a 6% employer match - A new Mac + $1,000 budget to set up your workstation or home office in your first year, then $500 every year thereafter - $1,000 quarterly AI Experimentation & Learning budget, so you can freely experiment with new AI tools to incorporate into your workflow, take courses, purchase educational resources, or attend AI-focused conferences and events - A team administrative assistant who can help you with personal and work tasks - You can find more reasons to work with us in this thread https://twitter.com/stuhlmueller/status/1694059800408269091! COMPENSATION For all roles at Elicit, we use a data-backed compensation framework to keep salaries market-competitive, equitable, and simple to understand. For this role, we target starting ranges of: - Senior (L4): $195-260k + equity - Expert (L5): $250-300k + equity - Principal (L6): >$270 + significant equity We're optimizing for a hire who can contribute at a L4/senior-level or above. We offer above-market equity for all roles at Elicit, as well as employee-friendly equity terms.
Research Engineer
Dyna Robotics builds general-purpose robots powered by a proprietary embodied AI foundation model with top-in-industry generalization and real-world performance. Already deployed with customers across multiple industries, our robots do commercial-grade work in the physical world. Our team comes from Google DeepMind, Meta, and Cruise, and we're backed by CRV, First Round, and other leading investors. THE ROLE Most ML infrastructure work ends at a benchmark. Ours ends at a robot doing real work at a customer site. You'll own our training and inference infrastructure end to end, from the moment robot data lands to the moment a new model runs on hardware. The goal: every GPU busy, every run reproducible, and every researcher's next experiment one command away. WHY THIS IS HARDER THAN TYPICAL ML INFRA - The data is physical: synchronized video, proprioception, and 3D signals from real robots, not clean text. - Latency is physical too: a slow model means a robot that hesitates or misses a grasp. - The loop is closed: data from deployed robots feeds back into training, and your systems sit at the center of that flywheel. WHAT YOU’LL DO - Scale distributed training across a multi-cloud GPU fleet using sharding, activation checkpointing, and memory optimization (FSDP, ZeRO). - Build a research codebase and scheduling system (Kubernetes/SLURM) built for fast iteration, automatic retries, and painless failure recovery. - Design high-throughput pipelines for terabytes of multimodal robot data so dataloaders never starve the GPUs. - Ship low-latency inference for real-time robot control using quantization, distillation, and compilation (TensorRT, Triton). - Profile GPU utilization, I/O bottlenecks, and memory fragmentation to get the most out of every node. YOU'LL THRIVE HERE IF YOU - Genuinely care about embodied AI. You follow robot learning research, have opinions about VLAs or world models, or have built something that moves. You want your work to show up in the physical world, not just on a dashboard. - Have 7+ years of engineering experience, including leading projects in HPC or ML infrastructure. - Know PyTorch and distributed training deeply (DeepSpeed, Accelerate, FSDP), including mixed precision and gradient accumulation. - Have hands-on experience with cloud GPU environments (GCP/AWS) and Kubernetes. - Understand distributed systems at a low level: race conditions, memory management, NCCL and inter-node communication. - Own what you ship: you design, build, and operate systems end to end to unblock fast-moving research. BONUS POINTS FOR - Robotics data formats (MCAP, Protobuf) or multimodal models such as VLAs. - Custom kernels (Triton), compilers, or runtime optimization. - Experience as a founding or early infrastructure hire. - Side projects involving robots, simulators, or hardware. At Dyna Robotics, we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect. Don’t let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you’re passionate about robotics, no matter your discipline, we want to hear from you, even if you don't check every box.
Applied AI Researcher, Post-Training
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used. Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org. KEY RESPONSIBILITIES - The Post-Training team focuses on adapting foundation models to real-world performance and alignment requirements. Researchers develop and evaluate techniques such as supervised fine-tuning, preference optimization (DPO, RLHF, RLAIF), and continual adaptation to align models with Distyl’s enterprise systems. The goal is to bridge raw model capability with trustworthy, contextually aligned system behavior - Researchers in Post-Training investigate new methods for aligning large models with human and system-level objectives. They explore trade-offs between generalization and specialization, data efficiency and robustness, capability and controllability. Their work informs how Distyl leverages foundation models safely, effectively, and at scale across industries WHAT WE REQUIRE - Deep Understanding of Post-training Techniques: Familiarity with supervised fine-tuning, preference optimization (RLHF/DPO), LoRA/PEFT, and instruction-tuning pipelines. - Experience Adapting Frontier Models: You’ve tuned or adapted LLMs/SLMs to specialized domains or behaviors through data curation, reward modeling, or continual pretraining. - Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.). - Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done. - Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow. - Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI. - Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize. WHAT WE OFFER - The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Software Test Engineer
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. THE OPPORTUNITY Deepgram is looking for a Software Test Engineer to design, build, and maintain automated test frameworks and exploratory test suites across our products, models, APIs, and data platforms. You enjoy breaking systems, probing edge cases, testing real-world and adversarial inputs, and automating repeatable validation so regressions are caught quickly. You translate product requirements and model metrics into automated regression tests, evaluation pipelines, data-quality gates, load tests, and release criteria. You partner with QA, Research, Product, Data, and Engineering to plan testing, execute human and automated evaluations, support user acceptance testing, and communicate risks clearly. When you find an issue, you provide precise reproduction steps, inputs, parameters, expected and actual results, and supporting data. What gets you excited? Building scalable automation that gives Deepgram confidence that its products, models, and data workflows work reliably for customers. WHAT YOU'LL DO - Define and execute well-designed test plans across Deepgram's products, APIs, SDKs, model-powered features, and data platforms, ensuring production software is robust, reliable, and performs well. - Design, build, and maintain automated test suites and frameworks for functional, integration, end-to-end, regression, API, browser, and service-level testing across batch and streaming workflows. - Translate product requirements and customer acceptance criteria into clear test strategies, repeatable test cases, and enforceable release gates. - Build and maintain representative, customer-focused, and adversarial test datasets, fixtures, and test environments that exercise real-world inputs, edge cases, failure modes, and system limits. - Validate model-powered behavior—including speech-to-text, text-to-speech, and other AI features—using appropriate metrics, expected outputs, human review, and regression coverage, while partnering with Research and model-evaluation specialists as needed. - Build testing infrastructure, including test harnesses, reusable scripts, test-data tooling, result-aggregation pipelines, dashboards, and visualizations that make quality signals easy to understand and act on. - Integrate automated tests, quality checks, canaries, and release validation into CI/CD so regressions are detected continuously rather than through manual testing alone. - Partner with Engineering, Product, Research, Data, Infrastructure, and DevOps to understand system behavior, dependencies, variations, performance limits, and deployment risks, and to establish appropriate test coverage. - Test data ingestion, processing, annotation, and quality-control workflows, validating data integrity, completeness, representativeness, deduplication, leakage, and downstream readiness. - Execute staging and production validation, load and reliability testing, cross-browser and customer-workflow testing, and user acceptance testing in partnership with internal stakeholders and customer QA teams. - Maintain and improve the test-case repository, automation coverage, test documentation, and release-readiness reporting so teams have a clear view of what was tested, what passed, and what remains risky. - Write precise, actionable bug reports with reproducible steps, inputs, parameters, expected and actual results, logs or artifacts, and clear severity; participate in triage and escalate issues when necessary. - Help raise the bar through code reviews, test-design reviews, technical discussions, and strong engineering, automation, and QA practices. WHAT WE'RE LOOKING FOR - BS, MS, or PhD in Computer Science, AI, Applied Math, or a related field, or equivalent experience. - 5+ years of professional software or QA engineering experience, with a track record of shipping test infrastructure or evaluation systems (senior candidates with significantly deeper experience welcome). - Solid backend/scripting experience in a language such as Python, Rust, Go, or similar. - Experience designing and building automated test pipelines, evaluation frameworks, or data-processing systems. - Strong analytical skills and comfort reasoning about metrics, thresholds, and statistical variation in results — able to distinguish real regressions from noise. - Ability to take charge of ambiguous technical challenges and communicate effectively across research, engineering, and product teams. NICE TO HAVE / WAYS TO STAND OUT - Hands-on experience testing or evaluating modern AI systems such as LLMs, RAG pipelines, agents, or multimodal models, including analyzing model behavior and failure modes. - Experience with voice, audio, speech recognition, or real-time systems, and familiarity with metrics such as WER, MOS, latency, and time-to-first-byte. - Experience building or improving test, evaluation, benchmarking, or ML infrastructure used by multiple teams or external users. - A strong appreciation for test and evaluation quality, including correctness, reproducibility, determinism, and consistency across environments. - Experience building test tooling for React Native, mobile applications, or other cross-platform environments that extends validation beyond the desktop. - Familiarity with cloud infrastructure, containers, ephemeral test environments, CI/CD systems, and monitoring tools such as Grafana, canaries, and anomaly detection. - Experience serving as a technical bridge across teams or platforms—including product, QA, evaluation, training, inference, data, or agent frameworks—with the communication skills to build alignment and influence decisions. - Prior involvement in open-source projects through contributions, reviews, maintenance, or community engagement. - Experience with voice, audio, speech recognition, or real-time systems, and familiarity with metrics like WER, MOS, or latency/TTFB. - Prior involvement in open-source projects, through contributions, reviews, maintenance, or community engagement. - Experience acting as a technical bridge across teams or platforms (evaluation, training, inference, agent frameworks), combining architectural understanding with clear communication and influence. - Familiarity with cloud infrastructure, containerized/ephemeral environments, and monitoring tooling (e.g. Grafana, canaries, anomaly detection). Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
AI Forward Deployed Engineer - Sweden
AI Engineer - FDE (AI Forward Deployed Engineer) Req ID: CSQ427R333 Preferred locations: Stockholm, Sweden. Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specialisations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Reporting to: Senior Manager - AI FDE, EMEA The impact you will have: - Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems - Own production rollouts of consumer and internally facing GenAI applications - Serve as a trusted technical advisor to customers across a variety of domains - Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally - Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: - Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy - Expertise in deploying production-grade GenAI applications, including evaluation and optimisations - Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. - Experience building production-grade machine learning deployments on AWS, Azure, or GCP - Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience - Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike - Passion for collaboration, life-long learning, and driving business value through AI - [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets - Willing to travel once every 4-8 weeks to see customers (as needed) About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
AI Forward Deployed Engineer - Netherlands
AI Engineer - FDE (AI Forward Deployed Engineer) Req ID: CSQ427R333 Location: Location: Amsterdam, Netherlands - Candidates to be based in the Netherlands region only (no remote working available from any other country) Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Reporting to: Senior Manager - AI FDE, EMEA The impact you will have: - Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems - Own production rollouts of consumer and internally facing GenAI applications - Serve as a trusted technical advisor to customers across a variety of domains - Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally - Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: - Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy - Expertise in deploying production-grade GenAI applications, including evaluation and optimizations - Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. - Experience building production-grade machine learning deployments on AWS, Azure, or GCP - Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience - Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike - Passion for collaboration, life-long learning, and driving business value through AI - [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets - Willing to travel once every 4-8 weeks to see customers (as needed) About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Vice President, Product Management, Managed AI
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About the Role: Crusoe's Managed AI Services portfolio launched in late 2025 and is scaling fast: We have already secured triple-digit $M ARR commitments from customers. The portfolio spans Managed Inference (Serverless, Self-Deployed and Tailored Deployment), Serverless Fine Tuning, with Serverless Reinforcement Learning and Agent Sandbox GA landing in H2 2026. As VP of Product Management, you will own the vision, strategy, execution and roadmap for this business, reporting to the SVP of Product Management and partnering directly with the VP Engineering for Managed AI Services. You will lead the portfolio as a business and via strong cross-functional partnerships, anchored in the rise of open models and Crusoe's vertically integrated cloud strategy from electrons to tokens. What You'll Be Working On: - Define the long-term vision, strategy and roadmap for the Managed AI Services portfolio, aligned to customer needs, company goals, market trends and GTM strategy - Build, lead and mentor a team of product managers, owning their performance and development - Partner with engineering, technical program management, product partnerships, marketing, customer success and sales to define requirements, prioritize features and drive the lifecycle from concept through launch and adoption at scale - Own the business metrics for the portfolio, including usage, reliability and production KPIs, pipeline, revenue, gross margin and customer satisfaction, and use that data to drive decisions - Shape go-to-market with sales, marketing and customer success, including positioning, messaging, pricing, routes-to-market and partnerships - Build relationships with key customers, ecosystem partners and GTM partners, translating their feedback into product improvements and working alongside the Director of Product Partnerships on partnership and M&A opportunities - Track the Managed AI competitive landscape and emerging technologies to inform strategy and surface new opportunities - Proactively identify and resolve technical and commercial risks, infrastructure bottlenecks and scaling challenges, and manage product budgets and resources against business goals What You'll Bring to the Team: - Proven product management track record with AI/ML services, including experience building AI managed services and scaling them from scratch - First-hand experience with AI managed services such as inference, tuning, reinforcement learning and agent sandboxes, along with the observability and evaluation practices that support them - Strong understanding of cloud infrastructure technologies and trends, ideally as a builder of planet-scale cloud products at a hyperscaler, neocloud or specialized inference provider - Experience managing and launching technical products and features for AI-native, digital-native and enterprise customers - Proven experience building, leading and mentoring product management teams - Strategic leadership: the ability to set a clear vision, make informed decisions with incomplete information, and guide a cross-functional team toward market awareness, adoption, revenue and gross margin goals - Analytical rigor: comfort interpreting complex market, customer and production data to drive product strategy - Excellent communication and collaboration skills, with the ability to present technical concepts, connect them to business outcomes and build consensus across diverse stakeholders - Hands-on use of AI tools to accelerate the product management craft Bonus Points - Experience leading a technical customer-facing team or operating an AI managed service from the customer or user side - Engineering background prior to moving into product management - Experience with open model ecosystems and the fine-tuning and inference optimization workflows enterprises use to adapt models to their data - Familiarity with Agile and Lean product management methodologies Benefits: - Competitive compensation and equity packages - Restricted Stock Units - Paid time off, paid holidays & leave of absence programs - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off - Global travel insurance & emergency assistance - Daily meals allowance - Additional perks & programs specific to location Compensation Range Compensation will be paid in the range of up to $345,000 – $385,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Customer Success Manager, Managed Inference
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role: We are seeking a motivated Customer Success Manager to support customers running AI inference workloads on Crusoe's cloud platform. Sitting within the Customer Experience organization, this role helps clients navigate the operational and technical challenges of deploying and scaling AI applications — from model serving and GPU utilization to production readiness. You will support customer relationships, act as a bridge to our technical teams, and help clients maximize the value of our AI and ML solutions. This is a full-time position based in the Bay Area, CA. What You'll Be Working On: - Build and maintain strong customer relationships, understanding their business needs and technical requirements as they deploy inference workloads. - Provide technical guidance to customers implementing and optimizing our cloud-based AI and ML solutions, including Kubernetes, model deployment, autoscaling, and observability. - Conduct regular reviews and report on customer progress against key performance indicators, monitoring adoption, inference consumption, latency, and uptime to surface growth opportunities and risks. - Coordinate with Product, Engineering, CS, and Solutions teams to surface customer challenges and advocate for customer needs on inference platforms and AI services. - Deliver training sessions and workshops to customers on the use and benefits of our products and services. - Address and resolve customer concerns, supporting customers during escalations and service incidents and escalating complex issues as needed. What You'll Bring to the Team: - Bachelor's degree in Business, Engineering, or a related field. - 2+ years of experience supporting enterprise cloud, AI, machine learning, developer platform, or infrastructure customers in a customer success, technical account management, or similar role. - Solid technical foundation in cloud computing platforms, AI, and ML technologies, with the ability to communicate complex concepts in simple terms. - Working understanding of inference workloads, model serving architectures, Kubernetes, containers, APIs, and GPU infrastructure. - Excellent interpersonal, communication, and presentation skills, with the ability to engage technical customer teams including AI, ML, and Platform Engineers. - Comfortable working in a fast-paced environment with ambiguous and/or iterative fact-sets. Bonus Points: - Familiarity with LLMs, RAG architectures, agentic applications, and inference optimization concepts. - Experience supporting Managed Inference, model serving platforms, or GPU-based inference environments. - Experience contributing to customer case studies or advocacy programs. Benefits: - Industry competitive pay - Restricted Stock Units in a fast growing, well-funded technology company - Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents - Employer contributions to HSA accounts - Paid Parental Leave - Paid life insurance, short-term and long-term disability - Teladoc - 401(k) with a 100% match up to 4% of salary - Generous paid time off and holiday schedule - Cell phone reimbursement - Tuition reimbursement - Subscription to the Calm app - MetLife Legal - Company paid commuter benefit; $300 per month Compensation Range Compensation will be paid in the range of up to $175,000 – $200,000 OTE. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Senior Forward Deployed Engineer (AI Agent)
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences. Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta. About the role: At Cresta, the AI Agent team is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable. As an AI Agent Engineer , you'll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.. This position requires strong engineering skills, adaptability, and customer engagement. If you are self-driven, analytical, and eager to leverage AI in practical applications, this role is for you. What You'll Do : - AI Agent Development: Develop, configure, deploy, and optimize AI agents using Cresta’s AI platform and tools. - System Integration: Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration. - Performance Optimization: Optimize AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments. - Requirements Gathering: Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions. - Demos & Iteration: Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives. - Project Coordination: Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams — identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings. - Partner Cross-Functionally: Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximize customer ROI. - Technical Guidance: Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. Provide technical guidance on AI agent best practices, including architecture design, security considerations, and scalability planning. What We're Looking For: - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. - Experience: 3+ years of full-time working experience in software development/Consulting, AI/ML engineering, or Forward Deployed Engineering. - Programming Skills: Proficiency in Python and Golang, with the ability to write clean, efficient code. - AI/ML Knowledge: Familiarity with AI/ML concepts. Hands-on experience with large language models (LLMs), and prompt engineering techniques are strongly preferred. - AI Agent Frameworks: Strong understanding of general AI agent frameworks, function calling, and retrieval-augmented generation (RAG). Hands-on experience of building such a system is strongly preferred. - Cloud & DevOps: Experience with cloud platforms (AWS, GCP, or Azure) and DevOps practices (CI/CD, containerization, monitoring). - Integration Expertise: Hands-on experience with integrating systems via APIs, webhooks, and data pipelines. - Communication: Excellent communication and project management skills. - Analytical Approach: Ability to use data-driven decision-making, including A/B testing and performance monitoring, to refine solutions. - Collaborative Builder: You thrive in cross-functional environments, working hand-in-hand with PMs and engineers to turn real customer problems into scalable AI solutions. Note on Our Hiring Process We highly value your time and engineering craftsmanship. To ensure a streamlined and objective process, the first step for qualified applicants following an initial resume review is a self-paced CoderPad technical assessment. This allows you to showcase your practical coding and problem-solving skills in a real-world environment before moving into conversational interview rounds. Perks & Benefits: We offer a comprehensive and people-first benefits package to support you at work and in life: - Comprehensive medical, dental, and vision coverage with plans to fit you and your family - Flexible PTO to take the time you need, when you need it - Paid parental leave for all new parents welcoming a new child - Retirement savings plan to help you plan for the future - Remote work setup budget to help you create a productive home office - Monthly wellness and communication stipend to keep you connected and balanced - In-office meal program and commuter benefits provided for onsite employees Compensation at Cresta: Cresta’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table. The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family. Base Salary Range : $185,000–$235,000 + Annual Bonus & Offers Equity Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email). Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed. Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta .ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.
Senior Systems Engineer, Enterprise AI Platforms
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . What You'll Do: IT Engineering at CoreWeave designs, builds, and operates the systems that enable our employees and acquired organizations to work securely and efficiently at scale. The team partners closely with Security, Business Development, PeopleOps, and Corporate functions to deliver resilient, standardized, and automation-first IT solutions that support CoreWeave's rapid growth. About the role: CoreWeave is hiring a Senior AI Platform Engineer to own the design, implementation, and governance of AI across CoreWeave's employee environment. You'll be the technical owner for the AI tools our employees use every day, on every surface they ship on: chat assistants, desktop apps, coding agents, AI terminals, AI browsers, workplace knowledge tools, and whatever comes next. You'll make them safe to adopt by building CoreWeave's guardrails directly into the platform through identity, device, and tenant-level controls rather than policy documents alone. This role is for someone who is genuinely passionate about AI and lives on its bleeding edge: someone who is already tuning agent behavior every week, has run swarms of agents and agent loops rather than just chatted with a model, and wants to keep learning at the velocity this field now moves. The tools, models, and best practices in this job will change monthly. That should excite you, not exhaust you. This is not a traditional AI/ML engineering role, and it is not a traditional IT administration role. It is deliberately a composite role that combines three things: production software and SRE engineering, hands-on LLM and agent work, and enterprise IT controls across identity, devices, and SaaS. We expect strong candidates to arrive deep in two of the three and grow into the third. Tell us which two. What success looks like in the first year: CoreWeave employees get frontier AI capabilities before almost any enterprise on earth. When a vendor ships a new model, agent surface, or feature, you already know it's coming; you're plugged into vendor roadmaps, betas, and the community and you have an evaluated, governed rollout ready in days, not quarters. That speed is possible because of the foundation you build in year one: sanctioned tools governed through identity, a connector and MCP allowlist in production, an intake process so "is this allowed" has an answer, internal agents shipping through an IT-owned gateway, and leadership visibility into usage, cost, and risk. The foundation is the floor; the pace is the job. AI platform lifecycle and governance - Own the end-to-end lifecycle of employee-facing AI platforms across every surface they ship on (web, desktop, mobile, IDE, terminal, and browser): evaluation, procurement support, tenant design, rollout, configuration management, and ongoing operations. - Keep the Platforms in Scope list current as the market moves. - Establish CoreWeave's AI operating framework for IT: intake and review for new AI tools and agents, standards for internal bots, runbooks, a clear path from pilot to supported service, and enablement content that helps employees use AI tools well and safely. Guardrails as enforceable controls - Design and implement AI guardrails as enforceable controls, in partnership with Enterprise Security and IT Identity and Access: SSO and SCIM provisioning, role- and group-based feature entitlement, data-retention and training opt-out settings, browser-extension and desktop-app policy, and device-trust requirements for access. - Build and operate connector and MCP allowlists with data-source scoping across Okta, Google Workspace, Slack, Atlassian, GitHub, ITSM, and HRIS. - Partner with Enterprise Security, Legal, and Privacy to translate acceptable-use, data-classification, and regulatory requirements into technical policy, and support audits with the evidence those controls produce. Infrastructure you'll own - The IT-owned control layer for CoreWeave's internal chatbots and agents: the gateway, identity, secrets, MCP allowlisting, logging, rate limiting, and cost attribution in front of the serving stack, deployed on CoreWeave infrastructure alongside the teams that run it. - Inference endpoints, agent hosts, and developer AI tooling on managed devices, treated as managed endpoints with a lifecycle, configuration baselines, and observability. - The IT-owned share of CoreWeave's internal MCP servers, reusable agent skills, and shared agent configuration (system prompts, AGENTS.md and CLAUDE.md instruction files, tool policies), plus the identity, logging, and allowlisting standards, with reference implementations, that agents and MCP servers built by other teams must meet. Operations, reliability, and telemetry - Hold the AI services you own to SRE standards: automation and infrastructure-as-code for everything repeatable, reliability targets, on-call, and incident response. - Instrument usage, cost, quality, and risk telemetry across AI platforms, and build the dashboards and alerting that show leadership what is being used, by whom, and at what spend. - Serve as the senior escalation point for AI tooling issues. - Communicate clearly and proactively with executives, cross-functional partners, and employees. Who You Are: - 6+ years in software engineering, site reliability engineering, or IT systems engineering where you built and ran things in code, not just configured them. - 2+ years of hands-on experience building with or administering LLM-based products: API integration, prompt and tool design, retrieval pipelines, agent frameworks, multi-agent workflows and agent loops, or enterprise administration of tools such as Claude, ChatGPT Enterprise, Copilot, Gemini, Glean, or Rovo. You have shipped or run something with these, not just used them. - Strong software engineering skills in Python, Go, Rust, or TypeScript: you have built services and integrations that other people depended on and kept them running. - Experience operating services in production (containers, infrastructure-as-code, CI/CD, secrets management, and observability), or you have automated enterprise systems with code (Terraform for Okta or Google Workspace, CI/CD for device and SaaS configuration, API integrations a company depended on) and are ready to go deeper on containers and observability. - A working understanding of how enterprise IT control systems function, even if you have not administered them yourself: - Identity and access: how SSO, SCIM, SAML/OIDC, and OAuth grant, scope, and revoke access, and what Conditional Access, Device Trust, and Zero Trust mean in practice. - Endpoint and device management: how MDM and device-trust tooling enforce policy on a managed laptop or browser. - SaaS administration: how permission and data-sharing models in tools like Google Workspace, Slack, Atlassian, and GitHub decide who can see what. - Proven ability to produce clear technical documentation and lead complex, cross-functional technical initiatives. Preferred: - Real-world experience administering one or more of these at enterprise scale: identity (Okta or Entra ID), endpoint management (Apple MDM/DDM, Jamf, Kandji, Munki, Intune, Chrome Enterprise), or SaaS platforms (Google Workspace, Slack, Atlassian, GitHub). - Experience deploying and governing enterprise AI tools across a 1,000+ person organization. - Hands-on experience building custom Model Context Protocol (MCP) servers and integrations, authoring reusable agent skills, and shaping agent behavior through system prompts and repository-level instruction files (AGENTS.md, CLAUDE.md, or equivalent). - Working knowledge of data governance for AI: data classification, retention, training opt-out, DLP, and the audit and logging capabilities of the major AI vendors. - Experience self-hosting and serving models. - Familiarity with compliance frameworks such as SOC 2, ISO 27001, SOX, and GDPR, and with emerging AI governance standards such as NIST AI RMF and ISO/IEC 42001. Wondering if you're a good fit? You may be a great fit if you already run swarms of agents and agent loops for your own work; you've been the person who figured out how to say "yes, safely" to a new AI tool instead of "no"; you're curious about how an Okta policy or an MDM profile actually enforces a rule and you'd rather build the control than write the memo; you think endpoints are wherever work happens; and you love turning ambiguous governance requirements into concrete, automated, testable controls. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast. We're in an exciting phase of hyper-growth, embracing a little chaos while constantly learning and improving. Our teams care deeply about how we build and how we work together, guided by our core values: - Be Curious at Your Core - Act Like an Owner - Empower Employees - Deliver Best-in-Class Client Experiences - Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $182,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Senior Software and AI Engineer
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . About the Role: As a Software and AI Engineer, IT Systems, you’ll design and develop AI agents and first-party applications that bring intelligence, automation, and great user experience to CoreWeave’s internal ecosystem. You’ll work across the stack ranging from agentics frameworks (using iPaas platforms like Workato) or latest software frameworks from LangChain, LangGrapsh, Cohere, ChatGPT agentflow, OpenAI API, Gemini agent flow, or Glean API to rich, React-based interfaces and mobile experiences to robust backend services written in Node.js and Go. What You’ll Do: - Develop agents using AI capabilities into applications using frameworks such as LangChain, LangGraph, ChatGPT API, and Glean API - Design and build first-party web and mobile applications using React (TypeScript) and modern front-end frameworks - Develop scalable backend services in Node.js and Go for data processing, orchestration, and automation - Build internal AI agents and copilots that assist with tasks in Finance, Billing, and Supply Chain domains, integrating with systems like ERP, HRIS, MRP, DCIM, Data Warehouse among others - either natively or via an iPaaS like Workato or Boomi - Implement APIs and microservices that enable modular and event-driven application architectures - Leverage GenAI tools (Cursor, Claude, Copilot, ChatGPT Codex) to accelerate development, testing, and documentation - Ensure robust observability, maintainability, and security across the application stack - Collaborate with stakeholders in Finance, Accounting, Security, and Engineering to design intelligent, user-centered workflows Who You Are: - Programming Experience: 7+ years of professional programming experience in languages such as TypeScript, Python, Go, C++, C#, or Java , specifically for delivering production-grade cloud services. - Full-Stack Proficiency: Proven expertise in modern backend (e.g., FastAPI, gRPC ) and frontend technologies (e.g., React, Next ), including the development of scalable backend services in Node.js and Go. - AI/LLM Experience: Solid familiarity with Generative AI frameworks ( LangChain, LangGraph, ChatGPT API, or Glean API ) and experience shipping production-grade AI/ML/LLM-based applications, or strong desire to build them. - Architecture: Solid experience designing and implementing RESTful APIs, microservices , and event-driven integration architectures. - Cloud & DevOps: Strong understanding of cloud environments (AWS, Azure, or GCP), container orchestration (e.g., Kubernetes), and proficiency with DevOps and CI/CD principles . - Automation Tooling: 7+ years of experience in scripting (Python or Bash) for automation and tooling. Preferred: - Experience developing AI-powered or agentic applications integrated with complex enterprise data (ERP, HRIS, DCIM, Data Warehouse). - Proficiency with machine learning and data engineering platform tools (e.g., Ray, Kafka, Spark). - Experience with iPaaS platforms (Workato, Boomi) for building internal AI agents and copilots. - Exposure to the functional domains of Marketing, Finance, Billing, or Supply Chain where intelligent automation can drive measurable business efficiency. Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. - You love to leverage cutting-edge GenAI tools (like Cursor, Claude, or Copilot) to accelerate your own development, testing, and documentation processes. - You’re curious about designing solutions with user experience (UX) and long-term system maintainability as a top priority. - You’re an expert in collaborating with non-technical stakeholders (like Finance and Accounting) to translate complex needs into intelligent, user-centered, and secure workflows. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: - Be Curious at Your Core - Act Like an Owner - Empower Employees - Deliver Best-in-Class Client Experiences - Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $182,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Account Solution Architect
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . What You’ll Do: The infrastructure powering the AI era doesn’t sell itself, and the customers building on it don’t want to be sold to. They want a peer. You’ll work as part of a focused three-person team alongside one Account Executive and one Account Manager, together responsible for landing new accounts and expanding within them across the region. The customers you’ll work with are AI labs, research institutions, and enterprises running some of the most demanding GPU workloads in the world. This is a role for someone who shows up with substance, who can hold a real conversation about model training and MLOps tooling in the morning and cluster networking in the afternoon, and who finds the space between infrastructure and application more interesting than either on its own. About the Role: As an Account Solution Architect covering Northern EMEA, you’ll move across the full stack depending on what the customer needs, from ML training workflows and MLOps platforms like Weights & Biases to bare metal GPU infrastructure and physical AI deployments. This isn’t a role built around a single layer of the stack, but the majority of your conversations will live in the ML layer. You’ll be expected to go deeper than most when the infrastructure conversation demands it, while staying commercially aware enough to support both new logo pursuits and in-flight account expansion. This role requires up to 40% travel. In this role, you will: - Cover Northern EMEA, with a focus on the Nordics and Benelux regions (Sweden, Norway, Denmark, Finland, Netherlands, Belgium, and Luxembourg). - Work closely with one Account Executive and one Account Manager as a dedicated three-person unit, supporting the full land and expand motion across the region. - Lead technical discovery with prospects and existing customers to understand model training requirements, MLOps workflows, and infrastructure constraints. - Design and present solutions spanning ML infrastructure, GPU compute, storage, networking, Kubernetes-based orchestration, and MLOps tooling. - Run proof-of-concept engagements and architecture reviews, and see them through to a decision. - Act as the internal voice of the customer, feeding technical requirements and product gaps back to Engineering and Product. - Maintain clear documentation of customer architectures, solution designs, and outstanding technical questions. Who You Are: - 3+ years in a pre-sales, solutions engineering, or solutions architecture role, ideally with a focus on AI/ML platforms, cloud infrastructure, or HPC. - Strong working knowledge of ML training and inference workflows - you understand how models are built, optimized, and deployed, not just where they run. - Hands-on familiarity with MLOps platforms and the tooling AI teams use day-to-day, including experiment tracking, pipeline orchestration, and model serving. - Experience with AI frameworks such as PyTorch, TensorFlow, or JAX. - Comfortable going below the SaaS layer when the conversation demands it - GPU topology, network fabric, and cluster architecture shouldn’t be unfamiliar territory. - Hands-on experience with Kubernetes and containerized workloads at scale. - Strong communication skills - you can adjust your register from a research engineer to a VP of Infrastructure without losing credibility at either end. - Experience managing multiple concurrent opportunities across a geographic territory. - Fluency in English required; proficiency in Dutch, Swedish, Norwegian, Danish, or Finnish is a plus. Preferred: - Familiarity with NVIDIA GPU architectures (H100, A100, H200) and the software stack around them: CUDA, NCCL, cuDNN. - Working knowledge of high-performance networking concepts: InfiniBand, RDMA, RoCE, TCP/IP. - Background working directly with AI labs, research institutions, or enterprise ML teams. - Exposure to physical AI use cases and the infrastructure requirements they bring. - Experience with Salesforce, Jira, Confluence, or similar tools. Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. - You’re comfortable going one layer deeper than the demo - whether that’s a networking topology, a training job that won’t converge, or a rack layout question from a facilities team. - You’ve worked across more than one layer of the stack and find the intersections more interesting than any single discipline. - You thrive in a fast-moving environment and take ownership of your region like it’s your own business. - You’re a natural collaborator who makes the people around you - including your AE and AM - better at their jobs. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: - Be Curious at Your Core - Act Like an Owner - Empower Employees - Deliver Best-in-Class Client Experiences - Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). LIjobs What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Senior Software Engineer (Typescript / Frontend) -...
ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Backend development experience in TypeScript or Python, with a focus on API design and service architecture - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders - Strong frontend skills with TypeScript/JavaScript and React Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus - Experience building data-oriented interfaces and visualizations PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Senior Software Engineer (Backend) - AI/ML
ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - Developer Experience: Design and implement developer tools, SDKs, and documentation that enable users to leverage ClickHouse’s AI/ML capabilities. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Backend development experience in TypeScript or Python, with a focus on API design and service architecture - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus #LI-remote PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Software Engineer, Applied AI
ABOUT CLAY AI is unleashing the biggest wave of company creation in history. Clay's mission is to be the engine those companies use to grow to their full potential. Clay predicts the next best action for your business and then helps you take it. We started by aggregating the best data for B2B companies. Then, we built the infrastructure to run any personalized campaign on top of it, including emails, ads, landing pages, and workflows that make reps more productive. Now, we're building agents that can help grow your company for you. We're already helping thousands of customers — including Anthropic, OpenAI, Google, and Visa — go to market with unique data, signals, and AI research. In 2026, we raised a $115M Series D https://www.linkedin.com/safety/go/?url=https%3A%2F%2Fwww.nytimes.com%2F2026%2F09%2F09%2Fbusiness%2Fdealbook%2Fclay-ai-fundraising.html%3Fsmid%3Durl-share%26unlocked_article_code%3D1._1A.E5rN.MeYsbgEsUKbB&urlhash=XS4q&mt=4bpSf4a8omAKuAHqAqZx6C11QpbLK_QwIhSV7gSf4Wf9aywPF_KBSiX9IkWE1AhXBEjPH8mK6fAEN7CMFlpvo0lPAtKRjs-dhgzYqHiVKUMCRtw0jScFgxWCRRfYs4HCX0YL9L6PCQz-edBLinvRdU_TaVUL2dA3&isSdui=true&lipi=urn%3Ali%3Apage%3Ad_flagship3_feed%3BoQmIsufoRJm7X2HC5Rqd%2Fw%3D%3D at $7.1B Valuation led by Wellington — and are on track to cross $200M in revenue this quarter. We also launched a $1M Scholarship fund for GTME Education. Some things to know about us: - Our community http://community.clay.com includes 17,000+ customers, 200+ integration partners, 125+ agencies, 50+ Clay clubs https://luma.com/claylive, and 30k members on Slack. - Our culture https://nextplayso.substack.com/p/spotlight-clay is unique inside and outside of work. Our team members are also DJs, activists, writers, clowns, marathoners, skydivers, psychedelic therapists, social workers, and more. - All employees can work with world-class coaches who specialize in creativity, management, and more. - Our operating principles — including negative maintenance and non-attached action — guide our work. Read more about them here https://cdn.prod.website-files.com/61477f2c24a826836f969afe/685d83a71452245cc1129791_4d770abfd83e276ec15315a2e06945bd_Clay2025_OperatingPrinciples.pdf. - Read about us in the NYT https://www.nytimes.com/2025/08/05/business/dealbook/clay-ai-marketing-fundraise.html, Forbes http://google.com/search?q=forbes+clay&rlz=1C5OZZY_enUS1155US1155&oq=forbes+clay&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQABiABDIHCAIQABiABDIHCAMQABiABDIHCAQQABiABDIHCAUQABiABDIHCAYQABiABDIHCAcQABiABDIHCAgQABiABDIHCAkQABiABNIBBzkzM2owajSoAgOwAgHxBVAe8UAxJx_p&sourceid=chrome&ie=UTF-8, First Round Review https://review.firstround.com/podcast/inside-clays-unconventional-path-to-1-25b/, and more https://www.clay.com/press. Hear from our employees directly on our Glassdoor https://www.glassdoor.com/Overview/Working-at-Clay-EI_IE9850794.11,15.htm page! ABOUT THE TEAM Clay's product is increasingly powered by AI agents — systems that research, enrich, and take action on behalf of our users, not just generate text. These aren't lightweight copilots layered onto an existing product; they're long-horizon agents built to take on the kind of multi-step, judgment-heavy work that skilled GTM teams spend real time on today. Several teams are working on different layers of this: agents that execute real go-to-market workflows end-to-end, and the shared platform (harness, memory, tools, retrieval, evals) that those agents run on. This role is a shared entry point across those teams. Depending on your background and interests, you'll be matched to a specific team as you move through the process - but every team here is working on the same underlying problem: closing the gap between an agent that looks good in a demo and one that's dependable enough to run unattended in production. ABOUT THE ROLE You'll work closely with product, research-adjacent teammates, and other engineers to make sure agents aren't just capable, but reliable, steerable, and worth trusting with real work. That means the job isn't only about improving model behavior in isolation - it's about turning those improvements into measurable gains in task completion, reliability, and time saved for the people using them. WHAT YOU'LL DO Depending on the team, you might work on: Agent products - Design and iterate on agent behavior across real GTM workflows. For example, sourcing a Total Addressable Market (TAM) list, which in practice means navigating ambiguous Ideal Customer Profile (ICP) definitions, reconciling conflicting signals across data sources, and making judgment calls that experienced analysts spend real time on. - Map manual, multi-step workflows that GTM teams do today and turn them into agent-driven flows that are as good as, or better than, a human doing it by hand. - Build and run evals that measure whether an agent actually completed the task correctly - not just whether the output looked plausible - and use them to catch regressions and failure modes. - Analyze real failures in production and systematically improve robustness. - Work with product to take agent flows from early prototype through closed beta and into general availability, and help define what "good" looks like for each one. Agent platform & infrastructure - Build the core agent harness that other teams build on top of, including memory systems, tool infrastructure, and retrieval architecture - Improve agent performance through prompting strategies, tool-use design, and context construction - Design guardrails and safety checks so agents behave predictably in production - Build a cross-surface evals framework so every team building on the platform can measure quality, regressions, and performance the same way - Build feedback loops that turn real usage and production logs into better prompts, tools, and eval coverage over time - Support teams building their own forks or variants of the managed agent for their specific use case WHAT YOU'LL BRING - Experience building or shipping production systems with LLMs or agents. This might look like multi-step agent orchestration, prompting and tool-use design, retrieval, structured extraction, or fine-tuning. - Strong backend fundamentals in APIs, databases, distributed systems. - Experience with model or agent evaluation: designing evals, measuring regressions, or turning fuzzy quality questions into measurable signals - A systems-and-outcomes mindset. You care about whether the product actually works for users, not just about model metrics in isolation - Comfort debugging messy, real-world failures and a bias toward shipping and iterating quickly in a space where best practices are still being figured out NICE TO HAVES - Experience with agent frameworks, tool-calling systems, or retrieval architectures (vector search, hybrid search, RAG) - Experience building or maintaining eval/benchmark infrastructure for LLM-based systems, or running fine-tuning in production - Experience with GTM, sales, or marketing workflows (e.g. lead sourcing, enrichment, audience building) - Familiarity with Clay's stack: React, TypeScript, Python, AWS (Aurora/Postgres, ECS/Fargate, Lambda, OpenSearch, Clickhouse, Elasticache/Redis), Terraform, Datadog - A growth mindset - we're building a team that's curious, open-minded, and happy to invest in each other's learning, not just their own
Research Engineer - Auto Research
ABOUT CHAI DISCOVERY Chai builds the design suite for molecules. We train frontier models that learn the underlying foundations of biochemical structure and interaction, so scientists can move faster and pursue targets that other methods cannot reach. AI is reinventing life sciences the same way it reinvented software engineering, and Chai is at the forefront of this shift. Leading pharmaceutical companies like Eli Lilly https://endpoints.news/eli-lilly-chai-discovery-sign-ai-software-deal/, Pfizer https://www.forbes.com/sites/amyfeldman/2026/06/04/why-pfizer-and-eli-lilly-are-betting-on-this-13-billion-ai-drug-discovery-startup/, and Novartis https://www.chaidiscovery.com/news/novartis-partnership are adopting our platform to power their drug discovery programs. We value diverse perspectives and are ready to find greatness in unexpected places. ABOUT THE ROLE Build agent-powered systems and frameworks to improve model training, accelerate inference, and help our research organization move faster. Automate the research loop itself rather than just the models it produces, including the tooling and datasets that allow agents to run experiments, evaluate results and propose next steps. Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering. This is a chance to push the frontier of AI drug design, working alongside a rigorous and craft-obsessed team. ABOUT YOU Ideal backgrounds include deep industry experience working with top AI/ML teams on agent-powered software—with strong system design skills, proficiency in Python, and Pytorch or JAX fluency. We look for technical spikes where you have gone deep and demonstrated exceptional impact on real-world problems and systems. WE OFFER The opportunity to work at the vanguard of AI research and frontier biology, with world-class people, on a mission that matters. We protect & promote a culture of high velocity and ownership. We compensate our team accordingly.
Staff Software Engineer, GPU Inference
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. ABOUT THE ROLE Cerebras is building a new generation of disaggregated AI inference systems https://www.cerebras.ai/press-release/amd-and-cerebras-announce-industry-leading-ultra-low-latency-and-high-throughput-ai-inference that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine. We are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant. You will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers. RESPONSIBILITIES - Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure. - Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible. - Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack. - Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads. - Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication. - Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware. - Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases. - Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems. MINIMUM QUALIFICATIONS - 8+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems. - Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads. - Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software. - Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system. - Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology. - Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box. - Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production. - Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements. - Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion. - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience. PREFERRED QUALIFICATIONS - Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools. - Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms. - Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project. - Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures. - Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control. - Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling. - Experience optimizing Mixture-of-Experts or multimodal models. - Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap. - Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects. - Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems. - Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice.
Staff GPU Inference SDET
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. About the Role As a Staff GPU Inference SDET, you will be the founding quality, reliability, and validation lead for a new GPU Inference Development team. Working closely with engineering leads and cross-functional systems infrastructure teams, you will design, build, and scale the end-to-end release qualification and automated test ecosystem for our GPU inference stack and rack-scale accelerated compute fleets. In this high-impact role, you will be responsible for building automated test suites to validate multi-node GPU cluster bring-up, verifying prefill worker optimizations, testing open-source and custom serving engines, and ensuring numerical correctness and performance stability under real-world streaming workloads. You will be the primary technical anchor ensuring production-grade reliability, fault isolation, and peak inference performance across accelerated GPU infrastructure. WHAT YOU’LL DO Build GPU Release Qualification Systems: Design and implement automated test automation frameworks, regression gates, and release qualification pipelines for the complete GPU inference stack—spanning custom API services, model-serving workers, container runtimes, serving engines, driver stacks, and firmware. Inference Serving & Workload Validation: Benchmark and stress-test distributed LLM serving frameworks, focusing on prefill vs. decode worker performance, continuous batching, prefix caching, KV-cache efficiency, and tensor/expert parallelism. Performance & Performance Modeling Verification: Build automated workload replay and benchmarking tools to validate GPU performance models. Track critical serving metrics including Time-to-First-Token (TTFT), Inter-Token Latency (ITL), request throughput, tail latency (P99), and capacity efficiency. Numerical Correctness & Quality Gates: Build validation infrastructure to ensure model accuracy, precision stability (FP16/FP8/quantization), determinism, and output correctness across software updates, kernel fusions, and hardware revisions. Fault Injection & Fleet Resilience: Engineer chaos engineering and fault-injection suites to simulate node failures, inter-node network degradation, GPU memory leaks, driver/firmware mismatches, and automated recovery paths for multi-node GPU clusters. Observability & CI/CD Integration: Integrate automated test pipelines with telemetry tools (e.g., Prometheus, Grafana) to turn one-off investigations into repeatable engineering gates and continuous performance monitoring. REQUIREMENTS: 8+ years of software engineering experience as an SDET, Infrastructure Quality Lead, or Systems Test Engineer. GPU & Cluster Infrastructure Expertise: Hands-on experience bringing up, provisioning, and validating multi-node GPU clusters (NVIDIA or AMD ecosystem) across public cloud infrastructure or enterprise data center environments. Inference Stack Knowledge: Deep understanding of LLM serving engines and distributed runtimes, including prefill vs. decode disaggregation, KV-cache management, and dynamic batching. Automation & Scripting: Expert-level Python programming skills with extensive experience designing custom test automation frameworks, diagnostic tooling, and CI/CD integration. Orchestration & Networking: Strong proficiency with container orchestration tools (e.g., Kubernetes, Slurm, Ray) and high-performance cluster interconnects (e.g., InfiniBand, RoCE, NCCL). Failure Analysis & Debugging: Proven background in root-cause analysis across software/hardware boundaries, stress testing, and node failure simulation in distributed systems. NICE TO HAVES: - Direct experience with either AMD (ROCm / HIP) or NVIDIA software stacks. - Experience building workload replay tools, ML evaluation pipelines, or MLPerf Inference benchmark suites. - Familiarity with low-level kernel profiling tools (PyTorch Profiler, NVTX, ROCm profilers) or C++ Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice.
Software Engineer, GPU Inference
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. ABOUT THE ROLE Cerebras is building a new generation of disaggregated AI inference systems https://www.cerebras.ai/press-release/amd-and-cerebras-announce-industry-leading-ultra-low-latency-and-high-throughput-ai-inference that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine. We are hiring a Software Engineer to productionize and optimize our GPU serving stack, working across our custom inference APIs, the vLLM serving runtime, the AMD ROCm software stack, and rack-scale AMD GPU infrastructure, to make this new serving path reliable, numerically correct, observable, and exceptionally performant. You will write production code, establish operational practices for a new accelerator fleet, and drive improvements in time to first token, throughput, tail latency, and capacity efficiency. This is a hands-on role requiring deep debugging and optimization across application, runtime, distributed systems, and hardware layers. RESPONSIBILITIES - Productionize the GPU inference stack. Design, build, deploy, and maintain the complete GPU prefill path, spanning API services, model-serving workers, vLLM, PyTorch, ROCm, GPU nodes, networking, and rack-scale infrastructure. - Own GPU operational readiness. Establish deployment, upgrade, rollback, health-checking, capacity-management, and failure-recovery practices for the AMD GPU fleet. Build automation that makes driver, firmware, runtime, model, and container compatibility explicit and reproducible. - Drive reliability in production. Define service-level indicators and objectives for GPU-backed inference. Improve fault isolation, graceful degradation, automated recovery, incident response, and post-incident remediation across the serving stack. - Improve inference performance. Profile and optimize time to first token, request throughput, tokens per second per GPU, tail latency, GPU utilization, memory efficiency, and rack-level capacity under representative production workloads. - Optimize model-serving behavior. Tune and improve scheduling, continuous batching, prefix caching, KV-cache management, tensor and expert parallelism, request admission, quantization, graph execution, and distributed communication. - Debug across system layers. Diagnose complex failures and performance regressions across application code, vLLM, PyTorch, ROCm/HIP, collective communication libraries, kernels, drivers, firmware, networking, and hardware. - Ensure numerical correctness. Build validation and regression infrastructure for model quality, numerical accuracy, precision changes, quantization, determinism, and compatibility across software and hardware releases. - Build performance and correctness infrastructure. Develop representative benchmarks, workload replay tools, profiling automation, release qualification, dashboards, and regression gates. Turn one-off investigations into repeatable engineering systems. MINIMUM QUALIFICATIONS - 5+ years of software engineering experience, including substantial individual-contributor ownership of complex production systems. - Experience building, operating, or optimizing production inference systems for large language models, multimodal models, or similarly demanding GPU workloads. - Strong programming ability in C++ and Python, including experience with multithreading, concurrency, memory management, and performance-sensitive software. - Hands-on experience with a high-performance model-serving framework such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or an equivalent internally developed system. - Strong understanding of GPU execution and performance, including asynchronous execution, memory movement, synchronization, kernel launches, communication overhead, and profiling methodology. - Experience debugging distributed systems across multiple layers rather than treating the serving framework or accelerator runtime as a black box. - Experience with Linux, containers, Kubernetes or comparable orchestration systems, observability, CI/CD, and operating latency-sensitive services in production. - Ability to design rigorous benchmarks, interpret noisy performance results, identify bottlenecks, and translate findings into production improvements. - Strong communication and technical leadership skills, with a demonstrated ability to drive ambiguous cross-functional projects to completion. - Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience. PREFERRED QUALIFICATIONS - Experience with AMD Instinct accelerators and the ROCm ecosystem, including HIP, RCCL, rocprofiler, AMD SMI, AITER, hipBLASLt, Composable Kernel, or related libraries and tools. - Deep CUDA experience that demonstrates an ability to transfer GPU systems knowledge across accelerator platforms. - Experience modifying or contributing to vLLM, SGLang, PyTorch, Triton, TensorRT-LLM, or another open-source ML systems project. - Experience optimizing prefill-heavy or disaggregated prefill/decode inference architectures. - Understanding of KV-cache transfer, prefix caching, continuous batching, chunked prefill, request scheduling, and memory-aware admission control. - Experience with multi-GPU and multi-node inference, including tensor parallelism, pipeline parallelism, expert parallelism, RDMA, collective communication, and failure handling. - Experience optimizing Mixture-of-Experts or multimodal models. - Knowledge of GPU kernel optimization, operator fusion, graph capture, attention kernels, GEMM tuning, and communication/computation overlap. - Experience with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4, including validation of their numerical and model-quality effects. - Experience building numerical-comparison, determinism, model-validation, or performance-regression test systems. - Experience collaborating directly with accelerator vendors, framework maintainers, or open-source communities. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice.
Applied Researcher, Audio Post-Training
ABOUT CARTESIA Our mission is to architect AI that learns from and interacts with the world like humans do. We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences. We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI. ABOUT THE ROLE On the Audio Post-Training team, you’ll be building and improving the capabilities that define how the rest of the world interacts with our generative audio models. This team is where customer needs meet research, and covers the full spectrum of modeling from ideation through productionization. On any given day, you might design evaluations to reliably measure new capabilities, build processing pipelines to improve data quality, experiment with finetuning and reinforcement learning approaches to refine model behavior, and more. This role is broad, and cross functional. Members of this team should combine broad research experience with a deep care about building to solve for customer needs and a strong sense of end-to-end ownership. You should be excited to synthesize customer complaints into a holistic understanding of capability gaps, to drive research efforts across data, model training, and evaluation to close those gaps, and to communicate those improvements to product and customer stakeholders. Ultimately, you will be responsible for creating the model experience that the rest of the world sees. YOUR IMPACT - Collaborate with product teams to understand and prioritize customer asks - Cut through the ambiguity of vaguely described behavioral problems to make concrete research plans. - Ideate and experiment across the full modeling stack, including data processing, synthetic data, SFT, RL, and evals to solve for high priority model capabilities - Root cause failures in production models and understand how to fix them in future model iterations - Decide which features and capabilities are ready for public launch WHAT YOU BRING - Strong fundamentals in software engineering, machine learning, debugging complex systems, and the ability + desire to learn quickly. - Experience building and ensuring quality of large multilingual datasets. - Experience training and debugging generative models (speech, text, or multimodal), especially SFT, RL, synthetic data, and evaluation (both human and automated). - Excitement about solving problems grounded in real customer needs, not just benchmarks. - Bonus points if you have native proficiency in other languages! Note: Cartesia participates in E-Verify and will provide the federal government with Form I-9 information to confirm employment eligibility after hire. MORE DETAILS 🏢 In-office policy: We’re an in-person team based out of offices in 🇺🇸 San Francisco, 🇬🇧 London and 🇮🇳 Bangalore. We love being in the office, hanging out together, and learning from each other every day. 🌎 Visa sponsorship: We provide visa sponsorship support and assess each circumstance on a case-by-case basis. However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can't always guarantee success. Your Recruiter will work with you to understand your visa sponsorship needs from the first call. 🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way. 🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed. OUR BENEFITS (US EMPLOYEES ONLY) 💰 Compensation Competitive base salary alongside attractive equity package. 🩺 Health Insurance Fully covered medical insurance along with dental and vision for you and your family. 🧑🧑🧒🧒 Parental Leave 9 weeks paternity & 12 weeks maternity leave 🏦 401(k) 🚆 Commuter Allowance A monthly stipend to help you get to and from the office. 🏖️ Flexible PTO Take as much time as you need to recharge your batteries. 🍲 Meals & Snacks Lunch, dinner and plenty of snacks, provided daily. 🦖 Your own personal Yoshi OUR COMMITMENT TO EQUAL OPPORTUNITY Cartesia is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other legally protected status.
Machine Learning Researcher, Multimodal LLMs
MACHINE LEARNING RESEARCHER, MULTIMODAL LLMS Location: San Francisco, CA or Remote ABOUT BLAND At Bland.com http://Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Voice is quickly becoming the primary interface between businesses and their customers, and we are building the models and infrastructure that make those interactions feel natural, reliable, and genuinely human. We’ve raised $100M from leading investors including Emergence Capital, Scale Venture Partners, Y Combinator, and founders of Twilio, Affirm, and ElevenLabs. THE ROLE We are looking for someone to contribute to the development of our next-generation multimodal LLM stack, combining speech, text, tools, and real-time reasoning into a single unified system. You’ll be responsible for building industry-leading conversational AI models that power Bland's agent, and taking them all the way from idea to production. At Bland, we're not just thinking about text modeling. You will define how our agents listen, think, and act in real time, integrating streaming audio, tool execution, and dynamic context into a single coherent system. You will take ideas from research through production systems serving millions of calls per day. WHAT MAKES YOU A GREAT FIT Strong LLM / Multimodal Background - Experience with LLMs, multimodal models, or speech-language systems - Deep understanding of prompting, fine-tuning, and alignment techniques - Familiarity with neural audio codecs and modern multimodal LLM techniques Fast Experimental Loop - You can go from idea → dataset → experiment → conclusion in days - You know how to design experiments that actually answer the question Product Intuition - Strong sense for what makes an interaction feel natural vs robotic - Ability to translate abstract modeling ideas into user-facing improvements Builder Mentality - You take ownership from research through deployment - You thrive in ambiguous, fast-moving environments - You care about impact, not just elegance HOW YOU SHOW UP - You think in systems, not just models - You obsess over latency, correctness, and real-world behavior - You are comfortable discarding ideas quickly when data disagrees - You push toward simple abstractions for complex problems BONUS POINTS - Experience with real-time voice systems or conversational AI - Background in tool-using agents or agent frameworks - Experience with multimodal datasets (audio + text + actions) - Contributions to LLM or speech-related research or open source COMPENSATION & BENEFITS - Competitive salary: $160,000 – $280,000 - Meaningful equity - Full healthcare, dental, vision - Office in Levi's Plaza, SF - High autonomy, high impact Additional Information Bland is an equal opportunity employer. We are committed to proving equal employment opportunities to all qualified applicants and employees and do not discriminate based on any legally protected characteristic. Bland participates in the E-Verify employment verification program. All new hires are required to complete the Form I-9, and employment will be verified though E-Verify as part of the onboarding process.
Member of Technical Staff - Research Engineer
ABOUT BLACK FOREST LABS We're the team behind Latent Diffusion, Stable Diffusion, and FLUX—foundational technologies that changed how the world creates images and video. We’re creating the generative models that power how people make images and video—tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we're just getting started. Headquartered in Freiburg, Germany with a growing presence in San Francisco, we’re scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity. WHY THIS ROLE Large-scale training is where research ideas become real, and where many of the hardest problems are no longer cleanly separated into “research” or “engineering.” A promising architecture only matters if we can train it stably, efficiently, and correctly across large GPU fleets. In this role, you will be embedded in production training and help where the hardest systems and performance problems arise: attention performance, custom kernels, low-precision training, profiling, memory behavior, data movement, distributed training stability, and throughput regressions. You will work directly with researchers, but your output will often be code, measurements, kernels, debugging tools, and training-system changes that make better research possible. We are open to a range of seniority for this role. The common thread is deep technical ownership: you should be able to make progress in ambiguous training-system problems, verify your results, and own the outcome. WHAT YOU’LL WORK ON - Improve the performance, reliability, and numerical stability of production training runs for large multimodal generative models - Profile full training steps across model code, attention, kernels, data loading, encoders, communication, optimizer steps, checkpointing, and memory pressure - Implement and validate GPU-level optimizations: fused kernels, attention paths, low-precision matmuls, quantization kernels, CUDA/Triton/CuTe/CUTLASS experiments, and no-compile alternatives where they make sense - Push lower-precision training forward, including FP8 / MXFP8 / FP4-style paths, weight and activation quantization, accumulation choices, convergence risk, and quality tradeoffs against baseline training runs - Work with researchers to translate architecture changes into efficient training implementations, and help distinguish real model-quality progress from changes that only look good in a microbenchmark - Debug distributed training failures: NaNs, loss spikes, silent numerical drift, memory leaks, stragglers, bad nodes, NCCL issues, and throughput cliffs - Build benchmarking and profiling harnesses that make performance claims trustworthy across hardware, shapes, sequence lengths, and training configurations - Help the training team move quickly when an urgent bottleneck appears, while turning repeated failures into better abstractions and tools WHAT WE’RE LOOKING FOR - Experience working deeply on large-scale training systems, ideally as part of a training group working closely with researchers - Strong PyTorch fluency, including comfort reading and modifying low-level training code rather than only using high-level APIs - Experience with distributed training concepts such as FSDP, tensor/model/context/sequence parallelism, activation checkpointing, NCCL, and overlapping compute and communication - Hands-on experience improving training throughput, memory footprint, or stability in real training runs - Experience profiling GPU workloads with tools like Nsight Systems, Nsight Compute, torch profiler, trace viewers, or custom telemetry - Practical GPU performance judgment: you may use modern coding agents and tools as much as you want, but you need the understanding to verify correctness, numerical behavior, and performance, and to own the result - Understanding of low-precision training and quantization tradeoffs: FP8, MXFP8, FP4/NVFP4-style formats, scaling, accumulation, numerical validation, and convergence risk - Good research judgment: you can partner with researchers on ablations, understand what the measurements do and do not prove, and keep optimization work tied to model-quality outcomes - Comfortable operating in ambiguity: sometimes the task is a clean implementation, sometimes it is a production fire, and sometimes it is figuring out which of three plausible explanations is actually true We'd be especially excited if you: - Have supported or co-owned training for a frontier foundation model that shipped or reached a major release - Have written or substantially improved forward/backward GPU kernels, or have shown you can make progress on kernel-level work with strong measurement and validation discipline - Have worked on attention performance, variable sequence length training, non-standard attention patterns - Have experience on Hopper or Blackwell-class GPUs - Have worked on low-precision training - Have experience with diffusion, flow matching, DiT, and multimodal generative model training; if your deepest background is autoregressive or LLM training systems, you are excited to learn the diffusion and multimodal modeling stack quickly - Can move naturally between profiler traces, kernel code, distributed systems failures, and research discussions HOW WE WORK TOGETHER We’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process. Everything we do is grounded in four values: - Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful. - Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task. - Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect. - Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos. If this sounds like work you’d enjoy, we’d love to hear from you. Base Annual Salary: EU €130,000 - €240,000 + Equity US $180,000 - $290,000 + Equity
Machine Learning Engineer: Evaluation
JOIN THE TEAM BRINGING ADVANCED AUTONOMY TO THE BUILT WORLD At Bedrock, we're moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects. We're not here debating the future of AI. We're deploying it in the real world. In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction. This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us. Machine Learning Engineer: Evaluation Bedrock is bringing autonomy to the construction industry! We’re a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We’re looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real world. Your Mission: Translate the infinite nuance of the built world into actionable, AI-native evaluations that accelerate Bedrock Operator adoption. The ideal candidate has hands-on experience in building evaluation systems and designing and executing statistical tests to gauge performance deltas between system iterations. More importantly, you’ve iterated on complex ML systems run in production environments, and you understand the complexities that come with it. WHAT YOU’LL DO: DESIGN AND MAINTAIN EVAL SYSTEMS: - Build pipelines for measuring system performance – across open loop and closed loop simulation, hardware in the loop systems, and field data from Bedrock Operator equipped machinery. Excite other teams to gain insights earlier in the development cycle through streamlined workflows. DEVELOP METRICS: - Connect product goals and system behavior - by bridging real-world specification to measurable indicators from logged data. Empower confident decision making from parameter tuning to program planning by slicing through the noise and delivering objective insights. CLASSIFY DATA SOURCES FOR TRAINING AND TESTING: - Implement infrastructure and classifiers - to self-annotate data and allow creation of datasets for a variety of training and evaluation use cases. Leverage models to source rich annotations for massive datasets to accelerate model iteration. PREDICT SYSTEM PERFORMANCE: - Model metrics and interpret results - from various sources ranging from raw sensor data to key leading indicators. Determine whether new construction sites pose hidden challenges and drive business decisions about deployment readiness. WHAT WE’RE LOOKING FOR: - Engineers who are currently Senior or Staff level with 5+ years of professional software engineering, data science, or research experience - 2+ years of professional experience analyzing modern ML or robotics system performance on real-world problems - Proficiency in Python and a data warehouse query language and comfort with development on infrastructure within parallelized cloud-based frameworks - Strong statistical analysis skills (e.g. classification, model fit bias determination, hypothesis testing, and uncertainty quantification) - Experience working with large datasets ***Bonus points: We’re especially interested in engineers who have applied statistical backgrounds to ML research or real-world robotics applications. Bedrock Robotics is an Equal Opportunity Employer We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic. Reasonable Accommodations We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.
Technical Program Manager, Model Performance
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE The Model Performance organization at Baseten is looking to hire our first Technical Program Manager. This is a zero-to-one role in a team that is responsible for building the core algorithms and methods that power Baseten’s high performance inference stack. You won't inherit an existing program framework, you'll build one from the ground up: the planning structure, execution processes, metrics and the cross-functional alignment that a fast-growing organization needs. Your contributions will directly impact how fast our performance R&D gets productized. If you can drive turning a set of ambitious but loosely defined initiatives into a predictable, well-governed program, this role is for you. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Model Performance team: - How to build a day-0 API for Kimi K3 https://www.baseten.co/blog/how-to-build-a-day-zero-api-for-kimi-k3/ - How we built the new fastest API for GLM-5.2 https://www.baseten.co/blog/how-we-built-the-new-fastest-api-for-glm-52/ - Inference engineering for DeepSeek V4 Pro 0813 https://www.baseten.co/blog/inference-engineering-for-deepseek-v4-pro-0813/ RESPONSIBILITIES - Own execution across Model Performance's active project portfolio, freeing the team's technical leads to focus on technical direction rather than tracking. - Design and stand up the planning structures, operating cadences, and status reporting mechanisms that best fits the team’s DNA. - Coordinate model release and optimization programs end to end, including day-zero launches, sequencing the work across performance engineering, infra, and release stakeholders. - Drive cross-team alignment as scope expands from Model Performance Core into Model APIs and the inference production stack (BIS). - Surface risks and dependencies early, and keep leadership informed with clear, honest status. - Partner with engineering leads to design team structures and ownership boundaries as the org scales. REQUIREMENTS - Deep technical program management experience - you're already running programs of this scope at an organization of similar or greater complexity. - Experience program-managing model performance or inference optimization work - you understand how engines like vLLM, TensorRT-LLM, SGLang, or NVIDIA Dynamo fit into a production serving stack and can engage credibly with the engineers building on them. - Demonstrated comfort with ambiguity and zero-to-one program building, not just executing an existing framework. - Proven ability to influence without authority across engineers, managers, and leadership who don't report to you. - Excellent written and verbal communication, with the ability to make deeply technical programs legible to any audience. - High agency decision making that demonstrates ownership, accountability and a strong desire to get things done. NICE TO HAVE - Experience coordinating model release programs, including day-zero launches (ideally for large-scale models). - Prior hands-on software engineering background. - Deep learning performance optimization background, in training or inference, with inference preferred. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Software Engineer - Model Performance
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-source ML models, we look forward to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: - Baseten Embeddings Inference: The fastest embeddings solution available https://www.baseten.co/blog/introducing-baseten-embeddings-inference-bei/ - The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/ - Driving model performance optimization https://www.baseten.co/blog/driving-model-performance-optimization-2024-highlights/ RESPONSIBILITIES - Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, KV cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure. - Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vLLM, sglang, CUDA, and other libraries to debug ML performance issues. - Apply and scale optimization techniques across a wide range of ML models, particularly large language models. - Collaborate with a diverse team to design and implement innovative solutions. - Own projects from idea to production. REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. - Experience with one or more general-purpose programming languages, such as Python or C++. - Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching). - Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM. - Demonstrated interest and experience in LLMs. - Deep understanding of GPU architecture. NICE TO HAVE - Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs). - Experience with CUDA or similar technologies. - Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions. - Experience with Docker and Kubernetes. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
AI Inference Engineer
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Forward Deployed Engineer at Baseten, you will partner directly with customers to architect, build, and deploy high-scale production AI applications on Baseten’s platform. You’ll own the journey with customers from initial exploration to production deployment, translating ambiguous business goals into reliable, observable services with clear quality, latency, and cost outcomes. This role is a great fit for entrepreneurial engineers who want a front-row view into how modern companies adopt AI at scale and who enjoy working across product, software development, performance engineering, and customer-facing implementations. To be clear, this is an engineering role with hands-on coding and software development that also includes aspects of product management, technical customer success, and pre-sales solution engineering mixed in. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: - Forward Deployed Engineering on the frontier of AI https://www.baseten.co/blog/forward-deployed-engineering/ - The fastest, most accurate Whisper transcription https://www.baseten.co/blog/the-fastest-most-accurate-and-cost-efficient-whisper-transcription/ - Deploy production-ready model servers from Docker images https://www.baseten.co/blog/deploy-production-model-servers-from-docker-images/ - Deploy custom ComfyUI workflows as APIs https://www.baseten.co/blog/deploying-custom-comfyui-workflows-as-apis/ RESPONSIBILITIES - Develop and maintain software systems and product features using one or more general-purpose programming languages in a production-level environment, with a preference for Python due to its relevance in ML projects. - Drive customer impact by designing, implementing, and deploying Baseten solutions end-to-end (problem framing → evaluation → production deployment → monitoring). This involves working with customers’ engineering teams at every stage of the customer journey including: sales, implementation, and expansion. - Deliver with velocity: turn vague objectives into clear specs and well-defined PoCs so we can rapidly ship well-tested services and outcomes for our customers - Optimize and enhance AI/ML projects, contributing to the continuous improvement of our technical stack. This includes developing features and PRDs with other engineering and product orgs. - Own products and customer projects end-to-end, functioning as both an engineer, project manager, and product manager, with a focus on user empathy, project specification, and end-to-end execution. - Navigate ambiguity and exercise good judgment on tradeoffs and tools needed to solve problems, avoiding unnecessary complexity. - Demonstrate pride, ownership, and accountability for your work, expecting the same from your teammates. REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. - 2+ years of professional work experience in a fast-paced, high-growth environment. - Demonstrated experience with one or more general-purpose programming languages in a production-level environment, with a strong preference for Python. - Familiarity with AI/ML pipelines and the lifecycle of ML model development and deployment. - Strong communication skills, particularly on complex technical topics. - Experience in building or optimizing AI/ML projects is highly valued. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Applied AI Engineer
About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform , empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence. We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com , Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works. Note: Arize is a remote-first company but certain roles often appear at in-person events. The nature of this role requires candidates to be based in the San Francisco Bay metro area, though there isn't an in-office requirement. The Opportunity AI is rapidly transforming the world. Whether it's developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into various aspects of our daily lives. Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production. The Role We are looking for an AI Applied Engineer focused on developer growth. This team fits in developer advocacy in the product team, outside of core engineering, connecting product to the AI Engineer ecosystem. This role is ideal for people with an entrepreneurial mindset and passion to grow our developer community through code, education, content, and hack-a-thons. You will be joining a team of engineers, product and marketing with experience building the next generation of AI systems from agents to assistants to LLM applications. What You'll Do - Write code and build examples that our community can reference - agents & assistants in different frameworks - Create awareness through technical content that educates AI developers – e.g. Github repos, blogs, eBooks, product documentation, workshops, demos - Build out Claude code and Cursor skills for automating systems - Improve the growth marketing experience - Be the “voice of the AI engineer” across Arize’s base of users and the AI developer community at large - Serve as a product advocate for Arize's core SaaS or OSS offerings. Distill market insights and developer feedback to inform roadmap and GTM activities - Craft best practices and novel perspectives on troubleshooting and improving production ML models and LLM-powered applications - Plan and speak at Arize-hosted and industry events and conferences Who We're Looking for - Working knowledge of generative AI - Technical experience with the LLM app development stack (e.g. agents, orchestration frameworks, vector databases, evaluation libraries) with proficiency in Python - Engaged in technical communities via GitHub, Medium, DZone, Stack Overflow, Reddit, LinkedIn, etc. - A data-driven creative who thrives in ideating and delivering on novel activities that earn the attention and trust of AI/ML practitioners - A self-learner who isn’t daunted by technical complexity and welcomes the challenge to develop their own POV - Excellent written and verbal communication - Willingness to attend evening meetups and events in the SF Bay Area The estimated annual salary for this role is between $100,000 - $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support. While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces. More About Arize Arize’s mission is to make the world’s AI work—and work for people. Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale. Learn more about what we're doing here: https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/ https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/ Diversity & Inclusion @ Arize Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture - Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI - Culturally conscious events such as LGBTQ trivia during pride month - We have an active Lady Arizers subgroup
Software Engineer - Perception (Fallback Stack)
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co http://applied.co. We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions ABOUT THE ROLE As a Perception Software Engineer on the Autonomy team, you will build the perception system for L4 autonomous trucks operating at highway speeds. The stack combines state-of-the-art machine learning - multi-modal 3D detection, BEV representations, learned tracking - with rigorous classical perception: state estimation, multi-object tracking, and sensor fusion. You will own problems end-to-end, from model architecture and training through onboard deployment and on-road validation. This is safety-critical software: every capability passes formal simulation, closed-course, and safety sign-off gates before it reaches public roads. You will collaborate daily with behavior/planning engineers, systems and safety engineers, and validation teams. AT APPLIED INTUITION, YOU WILL: - Design, train, and deploy deep learning models for 3D object detection across LiDAR, camera, and radar sensors - Build multi-sensor fusion architectures that combine independent detection and classification streams - Characterize perception failure modes, build targeted evaluation sets, and hill-climb system-level metrics - Build and operate the data engine: shadow-mode comparison against production, automated data mining, and retraining loops - Contribute to camera- and LiDAR-based localization perception under degraded conditions - Take your work through the full safety validation pipeline before it operates on public roads WE'RE LOOKING FOR SOMEONE WHO HAS: - Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or a related field - 4+ years of professional experience in ML-based perception, computer vision, or robotics - Strong proficiency in Python and C++ - Hands-on experience training and deploying deep learning models in production (e.g., PyTorch) - Solid grounding in classical perception: multi-object tracking, state estimation, and 3D geometry NICE TO HAVE: - Experience working in modern ML-based perception for autonomous systems - Experience with multi-sensor calibration and fusion - Experience optimizing models for onboard/embedded GPU inference - Background in safety-critical or automotive software development - Experience in a startup or fast-paced environment Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact careers@applied.co. We will work with you!
Software Engineer - AI Engineering
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co http://applied.co. We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions MEET OUR SOFTWARE ENGINEERS! Meet some of our software engineers who are shaping the future of autonomy and delivering world-class solutions helping customers shorten time to market. Hear about what brought them to Applied Intuition, what’s kept them interested, and their advice to potential candidates. ABOUT THE ROLE We are looking for an AI engineer to join a small, high-impact team building the AI capabilities, agent frameworks, and app platform that power every Applied product and the workflows our own engineers rely on daily. This is a 0 to 1 role with real customer demand already behind it and the potential to scale into a major new business line. You’ll operate like a startup within a larger, well-resourced company – with the freedom to experiment, ship fast, and work directly with customers. AT APPLIED INTUITION, YOU WILL: - Design and ship the shared AI infrastructure, frameworks, and tooling that power AI capabilities across Applied’s products and toolings. - Partner with product teams to identify the highest-leverage AI use cases and take them from idea to production. - Serve as a GenAI/LLM expert across the company – owning best practices for architecture, safety, evaluation, and deployment. - Design, build, and ship agentic systems such as background coding agents, AI SRE tooling - Work directly with customers to understand their needs, demo capabilities, and shape the product roadmap. Both external customers and internal teams are your customers. WE'RE LOOKING FOR SOMEONE WHO HAS: - A Bachelor's degree in Computer Science, Software Engineering, or equivalent - 2+ years of experience building and deploying AI/ML-powered features & products - Hands-on proficiency working with LLMs and agentic architectures. - Strong software engineering fundamentals and a bias toward shipping production-quality code quickly - Comfort working across the stack, from backend infrastructure to APIs to frontend work. - A collaborative mindset and genuine enjoyment of customer interaction – both with external customers and internal teams who depend on your work. - Proven ability to take initiative and context-switch across multiple high-priority projects in a fast-paced environment NICE TO HAVE: - Practical ML literacy – you understand model evaluation, data pipelines, and the tradeoffs between approaches - Background in developer tooling, platform engineering, or internal productivity infrastructure - Experience working with autonomous vehicle systems or simulation software Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact careers@applied.co. We will work with you!
Senior Software Engineer - Perception
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co http://applied.co. We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions ABOUT THE ROLE As a Perception Software Engineer on the Autonomy team, you will build the perception system for L4 autonomous trucks operating at highway speeds. The stack combines state-of-the-art machine learning - multi-modal 3D detection, BEV representations, learned tracking - with rigorous classical perception: state estimation, multi-object tracking, and sensor fusion. You will own problems end-to-end, from model architecture and training through onboard deployment and on-road validation. This is safety-critical software: every capability passes formal simulation, closed-course, and safety sign-off gates before it reaches public roads. You will collaborate daily with behavior/planning engineers, systems and safety engineers, and validation teams. AT APPLIED INTUITION, YOU WILL: - Design, train, and deploy deep learning models for 3D object detection across LiDAR, camera, and radar sensors. - Build multi-sensor fusion architectures that combine independent detection and classification streams. - Characterize perception failure modes, build targeted evaluation sets, and hill-climb system-level metrics. - Build and operate the data engine: shadow-mode comparison against production, automated data mining, and retraining loops. - Contribute to camera- and LiDAR-based localization perception under degraded conditions. - Take your work through the full safety validation pipeline before it operates on public roads. WE'RE LOOKING FOR SOMEONE WHO HAS: - Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field. - 5+ years of professional experience in ML-based perception, computer vision, or robotics. - Strong proficiency in Python and C++. - Hands-on experience training and deploying deep learning models in production (e.g., PyTorch). - Solid grounding in classical perception: multi-object tracking, state estimation, and 3D geometry. NICE TO HAVE: - Experience working in modern ML-based perception for autonomous systems. - Experience with multi-sensor calibration and fusion. - Experience optimizing models for onboard/embedded GPU inference. - Background in safety-critical or automotive software development. - Experience in a startup or fast-paced environment. Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact careers@applied.co. We will work with you!
Research Scientist (Research)
Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co http://applied.co. We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions ABOUT THE ROLE AND TEAM We are looking for multiple passionate Research Scientists to join the Research Group at Applied Intuition. The mission of the group is to create cutting-edge technology enabling next-generation physical AI, with emphasis on the two most challenging applications reshaping our everyday life: end-to-end autonomous driving and robotic generalist. We have a group composed of leading experts from top institutions and companies, recognized for their exceptional academic and industry contributions—including eight Best Paper awards at premier conferences and journals such as CVPR and ICRA. Learn more at appliedintuition.com/research http://appliedintuition.com/research. Supported by industry-leading tools and infra, researchers can access millions of miles of data from large fleets, and deploy methods they develop into various autonomous and robotic systems including self-driving cars/trucks, autonomous mining/construction machines, humanoid robots and dexterous hands. In addition to your research contributions, you will contribute to and learn from best practices in the autonomy and robotics industries within our fast-paced and customer-focused culture. Improvements deployed to our system immediately help our customers with their programs and deliver value to our business. We are open to all years of experience as long as the necessary requirements are met, including those with potential Tech Lead and Manager capacity. AT APPLIED INTUITION, YOU WILL: - Conduct research on reinforcement learning (RL) related topics including large-scale self-play RL, VLA post-training, large-scale closed-loop RL based on neural simulation with applications to autonomous driving - Diving into fundamental topics on RL with broader applications and potential imitative behavior learning incorporation, and relevant topics such as reward learning - Work closely with other Research Scientists and interns on research publications for submission to top-tier conferences - Collaborate with Research Engineers and engineering teams to test and deploy algorithms to our autonomy and robotics products WE’RE LOOKING FOR SOMEONE WHO HAS: - Strong research record in the fields of RL and VLA post-training for autonomous systems and robotics, with publications in top-tier conferences or journals in the fields of computer vision, machine learning, and robotics - MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely-related fields - 1+ year of research experience in autonomy, self-driving, or related field - Passion for next-generation, scalable autonomy and robotics for real-world systems - Strong research skills and the ability to work both independently and collaboratively on projects - Technical experience in: Python, Pytorch, computer vision, robotics systems, and distributed machine learning model training NICE TO HAVE: Hands-on experience in at least one of the following fields: - Self-play RL and imitation learning, behavior learning - VLA post-training for autonomy or robotics - Large-scale closed-loop RL in driving simulation - Large-scale RL training infrastructure (Ray preferred) Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact careers@applied.co. We will work with you!
Research Scientist/Engineer (Evaluations)
Application deadline: We are conducting interviews actively and aim to fill this role as soon as we find someone suitable. ABOUT THE OPPORTUNITY We’re looking for Research Scientists/Engineers for our pre-deployment team to work on Training-Run Assessments (TRAs). You will design and build automated pipelines for assessing whether egregious misalignment or scheming are emerging at any point of frontier post-training. This will involve evaluating and red-teaming of checkpoints at various stages of post-training as well as automated analysis of post-training data. You will get to work with frontier labs like OpenAI, Anthropic, and Google DeepMind and be among the first to interact with new models before anyone else. Our ideal candidate loves rigorously testing frontier AI models, and enjoys building efficient pipelines for automated analysis. KEY RESPONSIBILITIES Run and own pre-deployment engagements: We run a pre-deployment evaluation campaign with a frontier AI lab approximately every two weeks with thousands of runs across hundreds of distinct environments. We explore behaviors learned during training and check for undesirable behaviors like alignment faking, perform targeted follow-up experiments/red-teaming, and report our findings to the frontier AI lab we’re working with. Develop methodology for training-run assessments: in-between campaigns we improve our methodology, which might mean implementing new evals or building infrastructure for automated red-teaming. KEY REQUIREMENTS We don’t require a formal background or industry experience and welcome self-taught candidates. Software engineering skills: Our entire stack uses Python. We're looking for candidates with strong software engineering experience. Ideally, you have experience shipping and maintaining production Python code, and know how to factor messy problems into clean abstractions that others can use and extend. Data Analysis & Pattern Recognition: You can extract signal from large, messy datasets. You're comfortable with quantitative analysis and know when qualitative assessment is more appropriate. You can identify anomalies and unexpected model behaviors. Writing and communication: You succinctly convey qualitative and quantitative findings to a technical and non-technical audience. AI power-user: You’re capable of using AI to accelerate your work, technical or otherwise. You have experience using different models, know which ones to use for which tasks, when not to use AI, and always experiment with new AI workflows. NICE TO HAVE Experience thinking about AI risk topics like scheming and metagaming. Knowledge of LLM post-training: topics like RLHF, reasoning training, supervised fine-tuning, on-policy distillation, etc. We are using Inspect as our primary evals framework, and we value experience creating evals with it or similar frameworks like Harbor. We want to emphasize that people who feel they don’t fulfill all of these characteristics but think they would be a good fit for the position, nonetheless, are strongly encouraged to apply. We believe that excellent candidates can come from a variety of backgrounds and are excited to give you opportunities to shine. BENEFITS This role offers market competitive salary, equity, and competitive benefits. Salary: 100k - 200k GBP (~150k - 270k USD). We will be looking to meaningfully raise salaries soon. Flexible work hours and schedule Unlimited vacation Unlimited sick leave Up to 6 months of paid parental leave Comprehensive health, dental and vision insurance Retirement savings with competitive employer matching (e.g. 401(k) for US employees) Lunch, dinner, and snacks are provided for all employees on workdays Paid work trips, including staff retreats, business trips, and relevant conferences A yearly $1,000 (USD) professional development budget Relocation support and visa fees (if applicable) LOGISTICS Time Allocation : Full-time Location : This is an in-person role working out of our London or San Francisco office. We offer flexible working hours and wfh arrangements. Visa sponsorship: We sponsor visas in both the UK and US. Sponsorship isn't guaranteed for every role or candidate, but if we make you an offer, we'll work with you to find the right visa route
Software Engineer- Machine Learning
Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. About the Team At Anduril, our Battlespace Awareness Command and Control Software team specializes in solving complex, real-world problems through cutting-edge algorithms and intelligent software integrations. Operating in small, innovative teams, we push the boundaries of what's possible to deliver advanced technologies with mission-critical applications. Our commitment doesn't end with academic research or proof-of-concept experiments; we measure our success by the real-world impact of our deployed solutions. Our work involves cutting-edge algorithms and high-performance software for multi-target tracking, data fusion, battle management, autonomous robotic control, and mission planning. We are currently seeking talented technologists to join our mission and redefine the future of defense technology. About the Job We are looking to hire a Software Engineer to join our growing Battlespace Awareness team. In this role, you'll provide software engineering and development support for several of the team's core tools, and for candidates with an ML background, help stand up new ML infrastructure that improves how the team optimizes system parameters and detects performance regressions in CI. Required Qualifications - Professional experience in one or more of Python, Rust, C++, or C, with a clear track record of using these languages professionally - Solid software engineering fundamentals, including object-oriented programming, functional programming, and REST API design - Experience building low-latency or real-time software - Experience with software testing, including Robot Framework testing and integration test development - Comfortable using AI coding assistants (Claude or Codex) as part of your day-to-day workflow - Experience with GitHub and CI/CD pipelines - Machine learning background particularly in: - Hyperparameter optimization - Anomaly detection - Explainable ML (e.g., Bayesian ML) - Must be authorized to work in the United States - Eligible to obtain and maintain an active U.S. Secret security clearance Preferred Qualifications - TypeScript or JavaScript, React, and/or NodeJS - Pytorch - Python FastAPI - CesiumJS - Experience with faster-than-real-time (FTRT) simulation - Experience building Slackbot integrations. - Master's, PhD, or 2–3+ years of professional experience in machine learning, especially model deployment We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment. US Salary Range $191,000 - $253,000 USD The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including: Benefits At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits . Protecting Yourself from Recruitment Scams Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information. To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind: - No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates. - Please always verify communications: - Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address. - Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com . - Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links. - What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com . Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts. Data Privacy To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/ . By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.
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