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Senior Solutions Architect, Industrial Robotics
We are looking for a Senior Solutions Architect, Industrial Robotics to engage with customers, partners, and other NVIDIA software engineers to support applications and platforms that leverage NVIDIA technology that will be adopted across all industry segments. At NVIDIA, our Solutions Architects are drawn from elite developers and scientists who enjoy working with the latest in GPU and Networking hardware and software! NVIDIA’s platforms for machine learning, deep learning and high-performance computing have already made a major impact and are broadly used across leading North America companies. Our success has been based on vertical focus industry business development, building a strong developer ecosystem, and scaling out the business using a broad partner channel including HW OEMs, Cloud Service Providers, Global System Integrators, and VARs. A Solutions Architect is the bridge of technical expertise between our industry teams, our partners and our customers. Dynamically engaging with internal developers, scientific researchers, data scientists, IT managers, and senior leaders is an important part of the Solutions Architect role, and will give you experience with a range of partners and concerns. What you'll be doing: Partner with our industry and account teams to develop a keen understanding of customer goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs. Document what you know and teach others. This can vary from building targeted samples, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard. Be an industry leader with vision on integrating NVIDIA technology into Manufacturing use cases with AI, HPC, and enterprise GPU and networking architectures for advanced applications both in the datacenter and at the edge. Strategically partner with lighthouse customers and industry-specific solution partners targeting our computing platform. What we need to see: BS, MS, or PhD in Robotics, Engineering, Computer Science or equivalent experience. 8+ years of work-related experience in robotics, humanoids and AI domains - e.g. VLA, VLM, Transformers, Synthetic Data Generation software development with knowledge of parallel computing with GPUs. Background working with modern application deployment practices, including but not limited to Docker/Containers and Kubernetes. Experience with modern Deep Learning software architecture and frameworks. Strong written and oral communication skills with the ability to effectively collaborate with management and engineering. Experience supporting customers/partners in technical engagements. Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects. Strong analytical and problem-solving skills. Ways to stand out from the crowd: Experience applying AI to robotics and humanoid use cases, such as VLA, VLM training, simulation, and digital twins. Experience with frameworks like Tensorflow, Pytorch, TRT, and models like Vision Transformer. Background with NVIDIA simulation tooling like: Isaac Sim, Isaac Lab Experience using GPU programming, design practices and profiling tools like Nsight systems AI knowledge and expertise: Deep Neural Network research and development experience with specialized domains Published record of thought leadership in a technical area of simulation, robotics, data generation, AI OR Machine Learning research and development experience with industry data. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, results-oriented and enjoy learning while having fun, then what are you waiting for? Apply today! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 14, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Research Scientist - Autonomous Vehicles
We are now seeking a Sr Research Scientist for Autonomous Vehicles! NVIDIA is recruiting top Senior Research Scientists for Autonomous Vehicle Research! AI-powered autonomous vehicles that can learn, reason, and interact with people are no longer science fiction. Self-driving cars, autonomous delivery vehicles, and autonomous construction vehicles, among others, are getting increasingly close to widespread deployment. However, fundamental research questions still need to be addressed for us to achieve full vehicle autonomy. For instance, how can we: Enable novel training paradigms that leverage simulation to train AV policies in closed-loop? Equip autonomous vehicles with online and offline assurances that meet the standards for safety-critical systems? Ensure that autonomous vehicles work seamlessly in new places? These are some of the exciting questions that the NVIDIA Autonomous Vehicle Research group is tackling. We bring together a diverse, interdisciplinary research team working on core topics in vehicle autonomy, including agent behavior models, end-to-end AV architectures, AI safety, closed-loop training approaches, and AV foundation models (VLMs, reasoning models, etc.). Our focus is on basic and applied research; lab members are encouraged to publish their work and open-source code as well as provide real-world impact by deploying technology within production systems. NVIDIA is well known for its team culture, and lab researchers are able to closely interact with others within the company who are experts in perception systems, machine learning, and robotics. There is an opportunity to make a strong impact on products, while having the freedom and bandwidth to conduct ground-breaking publishable research. What you'll be doing: Designing and implementing cutting-edge techniques in the field of vehicle autonomy. Publish and present your original research, speak at conferences and events. Collaborate with other research team members, a diverse set of internal product teams, and external researchers. Have a broader impact through the transfer and/or open-source of the technology you've developed to relevant product groups. Collaborate closely with product teams to transfer research results into high-end, production-level systems. What we need to see: Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience). 6+ years of relevant research experience in the field of vehicle / robot autonomy. Strong knowledge of theory and practice of vehicle / robot autonomy, or a related area with a strong interest in connecting your work to autonomous vehicles. A track record of research excellence with your work published in top conferences and journals such as RSS, ICRA, IJRR, NeurIPS, ICML, CVPR, TAC, etc, and other research artifacts such as software projects Excellent collaboration and interpersonal skills Exceptional programming skills in Python; C++ and parallel programming (e.g., CUDA). Solid understanding of common machine learning frameworks such as PyTorch and Tensorflow. Strong communication and interpersonal skills are required along with the ability to work in a dynamic, research-focused team. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Developer Relations Manager
NVIDIA is the world leader in full stack AI Computing and in the last few years, with its unparalleled GPU based computers, has been powering up all of worlds of Generative AI, Agentic, Deep Learning, AI, accelerated data analytics, autonomous systems, robots around the world, Omniverse and now powers large language models and generative images/videos for the world. NVIDIA's customers include global tech-titans and span multiple verticals such as Manufacturing, Automotive, Aerospace, CSP, Healthcare, Telco, 3D Design, Simulation and others. NVIDIA is well positioned as the top ‘AI Computing Company’ delivering cloud ready solutions. This role is a key member of the NVIDIA team in India that would manage our startup, ISV and industry partners engagement in leading industries and to evangelize NVIDIA’s portfolio of technologies and accelerate its adoption among developers, mainly the Cloud native developers. Candidate should have strong technical and business competence with comprehensive India developer landscape understanding and the ability to be a leader who can function effectively and independently in a matrixed environment to groom and guide developers in above NVIDIA business domains. What you'll be doing: Your main responsibility will be to develop a technical and business strategy to win NVIDIA software and hardware platforms' adoption for the selected industries and verticals. The role requires a senior technical manager who believes that generative AI, deep learning, data science, and artificial intelligence is a new computing revolution and has the potential to transform every industry, with cloud first mind-set and strategy. Develop India NVIDIA developer ecosystem with cross-functional team; Product, Engineering, Software team, Solution Architects, Business, Marketing, Inception and Sales. Lead and develop strategic relationships with key AI Native startups, ISV’s, and leading industries’ developers. Know all NVIDIA AI computing platforms from Datacenter, Cloud to Edge and effectively articulate the value proposition to the India developer community while driving and leading strategic partnerships and community building among Cloud developers by running webinar, workshops, developer session and hosting technical meetups. Accelerate applications through the integrations of NViDIA libraries and drive the adoption of NVIDIA SDK’s and Software into developer products while being alert to the competitive landscape and communicate internally. Be NVIDIA technology mentor, evangelize the NVIDIA HW and S/W Solutions by being the focal point for the software developer community and occasionally lend some hands-on technical support. What we need to see: Bachelor's Degree in Engineering, Science, Technical or other related discipline or equivalent experience 8+ years of experience. Master's or Ph.D’s is preferred. Experience with cloud infrastructure platforms like AWS, Azure, Google Cloud, Tencent, Yotta, Baidu, OCI, ByteDance, etc and hands-on exposure in cloud technologies and microservices architecture. Understanding of virtualization and containerization technologies like Container, Docker, Kubernetes, VMware, KVM, etc. Expertise in C, C++, Python programming languages and GenAI, Deep Learning, Machine Learning, 3D Design/Simulation frameworks, while has developed related Cloud applications. Able to work independently and possess excellent communication skills to drive customer and internal engagements. You will ensure a positive experience for external customers/developers and partners while working cross functionally within our organization. Ways to stand out from the crowd: Experience in developing various applications in cloud environments, covering various industry vertical. Multi-year cloud-based development experience working on AI Deep Learning and Machine Learning Applications, AI Model Training/Inferencing and NVIDIA technologies and application domain. Excellent organizational, planning, and execution skills. Demonstrate ability to thrive in a dynamic environment that is experiencing rapid growth. NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to foster a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Senior Deep Learning Solution Architect
NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You'll Be Doing: Contribute to the development of open-source inference frameworks such as SGLang and vLLM, including feature and operator development, performance optimization, and model support, in collaboration with the community. Develop and optimize KV cache offloading frameworks for LLM workloads, supporting multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency. (Team project: FlexKV) Drive R&D on compute performance in distributed training, and explore methods and technologies for performance optimization. Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly. What We Need to See: Over 5 years working experience in the technology industry, with master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields. Strong interest in accelerated computing, parallel computing, and heterogeneous computing, with the motivation to explore these areas in depth. Solid programming skills, with a good understanding of data structures and computer systems fundamentals. Strong learning agility, adaptability, and the ability to analyze, define, and independently explore technical problems. Ways to Stand Out from the Crowd: Familiarity with heterogeneous computing, distributed training, parallel computing, or other areas related to high-performance computing. Experience in performance analysis, performance modeling, or performance optimization; contributions to open-source frameworks are a plus. Strong ability to define new problems and explore solutions; candidates with independent PhD-level research experience are preferred. Proficiency with AI coding tools. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.
Senior Deep Learning Frameworks Sustaining Enginee...
NVIDIA is hiring software engineers for its Deep Learning Frameworks Sustaining Engineering team. Our team produces software that's powering a revolution in deep learning, enabling breakthroughs in problems from image classification to speech recognition to natural language processing! Help us build software which will be used by the entire world by working directly with deep learning framework developers by integrating with open source code bases. What you'll be doing: In this role, responsibilities will include back-porting changes from the mainline branch, keeping track of open source dependency changes, and ensuring the latest stable dependencies are being used for our enterprise products. You will actively contribute changes to the team to support timely Long Term Support releases for the TensorFlow, PyTorch, TensorRT products. The scope of these efforts includes fixing customer reported bugs, integrating bug fixes found in mainline and working with other teams to ensure open source dependencies are patched for security vulnerabilities to address the needs of NVIDIA AI Enterprise business subscribers. What we need to see: Bachelors of Science in Computer Science, Deep Learning, Artificial Intelligence, Applied Math, or related field or equivalent experience. 5+ years of relevant software development experience Excellent C/C++ programming and software design skills, including debugging and open source integration. Python experience also helpful. Utilizing tools involved in building software (Make, Docker, Bazel), packaging systems (Debian, pip, npm, etc.), Build Systems (Gitlab, CI/Jenkins). Prior experience with machine learning algorithms and frameworks (TensorFlow, PyTorch, or MXNet). Ability to work independently, contribute to the stability of releases, and effectively communicate status to those involved in the release in a detail-oriented way. Ways to stand out from the crowd: GPU programming experience (CUDA or OpenCL) desired but not required Experience with contributions to or managing large open source project - use of github, bug tracking, branching and merging code, OSS licensing issues, managing patches, etc. Familiarity with Gitlab CI pipelines NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 218,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until January 13, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Technical Lead Manager, Autonomy Evaluation and In...
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We are looking for an Autonomy Leader to drive the technical roadmap for the systems that validate and verify the intelligence of the NuroDriver. In this role, you will lead the development of evaluation tooling that ensures our technology scales safely to millions of people. You will tackle real-world robotics challenges, bridging the gap between simulation and reality to improve everyday lives. - Intelligent Agents: Design and deploy "smart" evaluation agents that simulate complex interactions. - Intelligent Metrics: Design and deploy advanced algorithms that measure the cognitive performance of the ML models powering our self-driving car’s behavior, utilizing physics-based modeling and machine learning. - Close the Learning Loop: Leverage these evaluation frameworks to identify specific behavioral weaknesses in the NuroDriver, driving technical execution to refine the agent's decision-making logic. - Define the Technical Architecture: Work cross-functionally with Autonomy and Infrastructure engineers to set a roadmap that unifies evaluation frameworks, moving us toward automated, data-driven validation. About You We are looking for a leader who possesses deep technical judgment and the ability to inspire a world-class engineering team. Suggested Qualifications - Education: BS/MS/Phd in Computer Science, Robotics, Statistics, Physics, Math, or a related quantitative field. - Experience: 7+ years of industry expertise and a proven track record of driving team success through proactive mentorship and cross-functional initiative - Technical Expertise: You possess strong domain expertise in AI/ML, robotics, and/or large scale evaluation systems. You have the skills to evaluate complex trade-offs and exercise exceptional technical judgment. - Leadership: You can set an incredibly clear vision and earn the trust of a talented organization. You are capable of aligning the team behind a unified technical strategy. - Execution & Urgency: You possess an inherent sense of urgency and champion fast, high-quality technical execution. - People Management: Experience in hiring, organizing, and fostering a world-class engineering culture, with a passion for inspiring team members to grow their skills. - Collaboration: Ability to work closely with cross functional teams to manage dependencies and ensure the Autonomy team has the compute and infrastructure needed to succeed. At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $235,030 and $352,290 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP
Software Engineer, ML Infrastructure Platform
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Nuro takes a machine-learning-first approach to autonomous driving, and the ML Infrastructure team builds and operates the infrastructure that makes that possible. We own the systems that train the models at the core of the Nuro Driver™ - from distributed GPU training and closed-loop reinforcement learning, to the workflows, orchestration, observability, and cost management that keep the fleet running efficiently. Our work sits directly on the critical path of autonomy development. When a training run stalls, when a pipeline silently regresses, or when GPU utilization slips, it shows up in how fast the rest of the company can ship. We care as much about reliability and operational maturity as we do about raw scale. About the Work - Contribute to Nuro’s training infrastructure, spanning multi-generation accelerators, and multi-cluster scheduling and orchestration. - Design and operate large-scale data pipelines - batch and streaming ingestion, storage layout, and high-throughput data generation and storage. - Design and develop agentic-first ML workflows - data-to-training-to-evaluation pipelines that are introspectable, reproducible, and easy for autonomy teams to run and extend. - Own reliability for critical training and release pipelines: instrument them, define meaningful alerting, and build the on-call and incident-response practices that let the team catch regressions. About You - BS, MS, or PhD in Computer Science, Electrical Engineering, or a closely related field, plus 1+ years of relevant work experience. - Willingness to deep-dive into implementation and to raise the technical and operational standards of the broader engineering organization. - A demonstrated ownership mindset: you drive systems to operational maturity e.g. through monitoring, alerting, runbooks. - Strong proficiency in Python (and comfort with C++, Go or a similar systems language). - Hands-on experience running production infrastructure on Kubernetes. - Solid distributed-systems fundamentals and the ability to reason about performance, failure modes, and reliability across a complex system. Bonus Points - Strong working knowledge of GCP. - Experience with building large scale data generation pipelines. - Experience with Kubernetes-native orchestration for ML workloads. - Depth in GPU / distributed training internals, including NCCL and collective communication. - Familiarity with GPU and training observability tooling and using it to diagnose real bottlenecks. - A track record of driving down infrastructure cost while improving reliability. At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.
Software Engineer, ML Inference Platform
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work - Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models. - Develop and maintain continuous testing and monitoring systems for core ML infrastructure components. - Develop observability to track ML model lifecycles from data generation to on-road validation. - Maintain an in-house ML inference platform to serve large language models efficiently. - Maintain an in-house ML compiler platform to compile, deploy, and validate Nuro autonomy models to various hardware platforms. About You - You have a degree in BS, MS.c or Ph.D with 1+ years of relevant experience - Strong proficiency in Python or similar languages. Familiarity with c++. - Technical excellence: Develop with a high standard for performance, scalability, and code quality. - Domain experience: Experience working with ML pipelines; ability to understand and design complex distributed systems - Independence and productivity: Ability and willingness to dive into unfamiliar territory, learn fast, and improve complex systems. Bonus Points - Strong proficiency in C++ or other high-performance low-level languages - Experience working with large-scale distributed systems - Experience with system & framework design - Experience with data workflow orchestration platforms - Experience with ML compilers At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.
Senior/Staff Software Engineer, ML Inference Platf...
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work - Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models. - Develop and maintain continuous testing and monitoring systems for core ML infrastructure components. - Develop observability to track ML model lifecycles from data generation to on-road validation. - Maintain an in-house ML inference platform to serve large language models efficiently. - Maintain an in-house ML compiler platform to compile, deploy, and validate Nuro autonomy models to various hardware platforms. About You - You have a degree in BS, MS.c or Ph.D and 3+ years of relevant experience - Strong proficiency in Python or similar languages. Familiarity with c++. - Technical excellence: Develop with a high standard for performance, scalability, and code quality. Domain experience: Experience working with ML pipelines; ability to understand and design complex distributed systems - Independence and productivity : Ability and willingness to dive into unfamiliar territory, learn fast, and improve complex systems. Bonus Points: - Strong proficiency in C++ or other high-performance low-level languages - Experience working with large-scale distributed systems - Experience with system & framework design - Experience with data workflow orchestration platforms - Experience with ML compilers At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $352,290 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.
Senior Software Engineer, ML Infrastructure Platfo...
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Nuro takes a machine-learning-first approach to autonomous driving, and the ML Infrastructure team builds and operates the infrastructure that makes that possible. We own the systems that train the models at the core of the Nuro Driver™ - from distributed GPU training and closed-loop reinforcement learning, to the workflows, orchestration, observability, and cost management that keep the fleet running efficiently. Our work sits directly on the critical path of autonomy development. When a training run stalls, when a pipeline silently regresses, or when GPU utilization slips, it shows up in how fast the rest of the company can ship. We care as much about reliability and operational maturity as we do about raw scale. About the Work - Contribute to Nuro’s training infrastructure, spanning multi-generation accelerators, and multi-cluster scheduling and orchestration. - Design and operate large-scale data pipelines - batch and streaming ingestion, storage layout, and high-throughput data generation and storage. - Design and develop agentic-first ML workflows - data-to-training-to-evaluation pipelines that are introspectable, reproducible, and easy for autonomy teams to run and extend. - Own reliability for critical training and release pipelines: instrument them, define meaningful alerting, and build the on-call and incident-response practices that let the team catch regressions. About You - BS, MS, or PhD in Computer Science, Electrical Engineering, or a closely related field, plus 3+ years of relevant work experience. - Willingness to deep-dive into implementation and to raise the technical and operational standards of the broader engineering organization. - A demonstrated ownership mindset: you drive systems to operational maturity e.g. through monitoring, alerting, runbooks. - Strong proficiency in Python (and comfort with C++, Go or a similar systems language). - Hands-on experience running production infrastructure on Kubernetes. - Solid distributed-systems fundamentals and the ability to reason about performance, failure modes, and reliability across a complex system. Bonus Points - Strong working knowledge of GCP. - Experience with building large-scale data generation pipelines. - Experience with Kubernetes-native orchestration for ML workloads. - Depth in GPU / distributed training internals, including NCCL and collective communication. - Familiarity with GPU and training observability tooling and using it to diagnose real bottlenecks. - A track record of driving down infrastructure cost while improving reliability. At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $291,150 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.
Senior Software Engineer, Behavior Planning
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The behavior team at Nuro develops the Nuro Driver’s prediction and planning systems to enable safe, driverless autonomy. We are looking for strong software engineers to research, develop, and implement technologies for Nuro’s planning stack to empower all rides on all roads. This encompasses building a generalizable and scalable ML planner that can power L4 driving for robotaxi applications as well as serve as an L2 solution for the largest auto manufacturers in the world. Operating domains of the Nuro Driver™ vary from structured surface streets and highways to more unstructured areas such as parking lot driving, parking and multi-point turns in busy traffic situations. You’ll be developing state-of-the-art algorithms to enable the Nuro Driver to safely and reliably plan and navigate complex situations in a human-like manner. You will work on intelligent strategies on how to leverage diverse data to have the biggest impact in our learned behavior stack. If you want to implement cutting-edge robotics and machine learning technologies in a collaborative environment with immediate impact, come and join us! About the Work - Design and implement novel robotics and machine learning technologies for the Nuro Driver. - Work cross-functionally with engineers across behavior, perception, mapping, and ML research to advance the state-of-the-art in autonomous driving. - Implement practical solutions with production-ready software, to deploy new technologies on real vehicle platforms in a safe, performant, and scalable way. - Provide technical guidance and mentorship to junior members of the behavior team About You - PhD or Masters Degree in robotics, computer science, mechanical/aerospace engineering, electrical engineering, mathematics, or related field. - Robotics expertise in areas such as path planning, motion planning, trajectory generation, behavior planning, optimal control. - Machine learning experience with techniques such as deep learning, reinforcement learning, imitation learning, transformers, and diffusion models. - Experience in optimizing model performance through efficient processing, visualization, and analysis of large datasets. - Strong software development skills and Python/C++ coding proficiency. - Ability to collaborate within and across teams and derive best solutions from cross-functional interactions. - Desire to work at the edge of research and development, bringing algorithms from research into production. - Bonus: hands-on experience developing software for safety-critical systems, distributed training, or inference optimization. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $193,930 and $291,150/year for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.
Research Engineer, Domain Scaling
NORMAL COMPUTING | BUILD WITH US Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul. THE ROLE The Domain Scaling team has the goal of making Normal’s Agents world-class at anything Chip-Engineering and EDA-related, UVM, debugging, analog, lean formalization, materials-aware optimization, etc. This is a unique role that combines executing directly on applied research and data sourcing (real-world and synthetic) to improve our models. You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance. WHAT YOU WILL OWN - Own the data strategy for knowledge work verticals end-to-end, from task sourcing through RL training - Build and manage relationships with external vendors, including outreach, evaluation of data quality, and reward design - Collaborate with domain experts to design data pipelines and evaluations - Explore novel ways of creating RL environments for high-value tasks - Develop and improve QA frameworks to catch reward hacking and ensure environment quality - Run generalization experiments to measure how data strategy changes improve model capabilities - Partner with other AI researchers and product teams to translate capability goals into training environments, evals, and real product features WHAT MAKES YOU A GREAT FIT - Have experience with post-training large language models for specific domains or real-world use cases - Have experience with reinforcement learning, reward design, or training data curation for LLMs - Are comfortable managing technical vendor relationships and iterating quickly on feedback - Find value in reading through datasets to understand them and spot issues - Have strong cross-functional collaboration skills - Are passionate about making AI more useful for chip development and recursive hardware self-improvement - Are excited about a role that includes a combination of applied research and hands-on data work BONUS POINTS - Have experience training production ML systems - Have experience designing evals or benchmarks for LLMs - Have domain expertise in a vertical where we would like to make our models more useful - Have experience working with external vendors or technical partners Equal Employment Opportunity Statement Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status. Accessibility Accommodations Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com. Privacy Notice By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Applicant Privacy Notice https://normalcomputing.com/applicant-privacy-notice.
Senior AI Framework Engineer
About Modular At Modular, a Qualcomm company , we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges. If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about our culture and careers to understand how we work and what we value. About this role At Modular, we are building a next generation AI platform to power modern applications and facilitate access to cutting-edge hardware. The MAX Framework is our developer-facing layer: it defines the APIs developers use to express models, integrate custom kernels, orchestrate execution, iterate on quality and ship systems into production. As an Senior AI Framework Engineer for MAX, you will own and evolve core APIs and developer experience for inference and training of AI models. You will work at the intersection of API design, systems engineering, and modern AI frameworks. Your output will be the specifications, abstractions, and reference implementations that make MAX feel coherent, powerful, and intuitive to use — while preserving performance, portability, maintainability and TCO. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office. What you will do Influence the design of the API surface for MAX: namespaces, core abstractions, extension points, programming model, compatibility guarantees and developer experience. Design inference APIs that support real-world serving needs: model loading, distributed inference, quantization, tokenization/pipelines, configuration surfaces, batching/streaming, and deployment-oriented ergonomics. Design training APIs that scale from single device to distributed execution, with clear primitives for device placement, parallelism, checkpointing, and observability. Create a coherent programming model across Python and Mojo-adjacent surfaces: align naming, types, and conventions; avoid leaky abstractions; define the "pit of success". Drive RFCs and technical specs: write and socialize proposals; gather feedback from internal model engineers and external users; iterate towards consensus. Partner cross-functionally with compiler/runtime, kernels, cloud/serving, and documentation/DevRel teams to ensure APIs map cleanly to underlying capabilities. Build reference implementations and exemplar code: golden-path examples, architecture templates, and best-practice patterns that teams can copy. Set quality bars for APIs: versioning policy, deprecation strategy, test strategy, and documentation requirements. What you bring to the table Significant experience designing and evolving developer-facing APIs (SDKs, frameworks, or platforms). Strong understanding of modern AI frameworks and their design tradeoffs (e.g., PyTorch, JAX, TensorFlow, vLLM, XLA/MLIR-adjacent ecosystems). Experience with inference and training systems (model execution graphs, compilation, runtime scheduling, distributed execution, checkpointing, performance tuning). Fluency in one or more systems / performance languages (C++, Rust, Go) and one or more user-facing languages (Python; familiarity with Mojo is a plus). Excellent taste for API ergonomics: naming, composability, types, error handling, configurability, and clarity. Strong written communication: you can write specs that engineers can implement without ambiguity. High engineering standards, pragmatism, and a bias towards incremental development without compromising long term design. What Modular brings to the table: Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders. World-class Benefits. In order to attract the best, we need to offer the best. Your benefits package may include comprehensive healthcare coverage, retirement and savings programs, employee stock purchase opportunities, paid time off, wellbeing resources, family support programs, and learning and development opportunities. Please note that specific benefit packages may vary based on your location, you can read more about benefits offered by Qualcomm here . Competitive Compensation. We offer very strong compensation packages, including RSU grants. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and share a purpose to fundamentally change how developers build and deploy AI systems. The estimated base salary range for this role to be performed in the US, regardless of the state, is $180,000–$324,000 USD . The estimated base salary range for this role to be performed in Canada, regardless of the province, is $172,400.00–$258,700.00 CAD . The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply, as we may have openings at lower or higher levels than the one advertised.
AI Framework Engineer
About Modular At Modular, a Qualcomm company , we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges. If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about our culture and careers to understand how we work and what we value. About this role At Modular, we are building a next generation AI platform to power modern applications and facilitate access to cutting-edge hardware. The MAX Framework is our developer-facing layer: it defines the APIs developers use to express models, integrate custom kernels, orchestrate execution, iterate on quality and ship systems into production. As an AI Framework Engineer for MAX, you will work with core APIs and developer experience for inference and training of AI models. You will work at the intersection of API design, systems engineering, and modern AI frameworks. Your output will be the implementations that make MAX feel coherent, powerful, and intuitive to use — while preserving performance, portability, maintainability and TCO. LOCATION: Candidates based in the US are welcome to apply. This role will be based at our Los Altos, CA headquarters (minimum 3 days per week on-site) with relocation assistance provided for out-of-state candidates based in the US. What you will do Develop the API surface for MAX: namespaces, core abstractions, extension points, programming model, compatibility guarantees and developer experience. Develop and design inference APIs that support real-world serving needs: model loading, distributed inference, quantization, tokenization/pipelines, configuration surfaces, batching/streaming, and deployment-oriented ergonomics. Develop training APIs that scale from single device to distributed execution, with clear primitives for device placement, parallelism, checkpointing, and observability. Contribute to a coherent programming model across Python and Mojo-adjacent surfaces: align naming, types, and conventions; avoid leaky abstractions; define the "pit of success". Work on technical RFCs and technical specs: write and socialize proposals; gather feedback from internal model engineers and external users; iterate towards consensus. Partner cross-functionally with compiler/runtime, kernels, cloud/serving, and documentation/DevRel teams to ensure APIs map cleanly to underlying capabilities. Develop reference implementations and exemplar code: golden-path examples, architecture templates, and best-practice patterns that teams can copy. What you bring to the table Passion for designing developer-facing APIs (SDKs, frameworks, or platforms). Good understanding of modern AI frameworks and their design tradeoffs (e.g., PyTorch, JAX, TensorFlow, vLLM, XLA/MLIR-adjacent ecosystems). Proficiency in one or more systems / performance languages (C++, Rust, Go) and one or more user-facing languages (Python; familiarity with Mojo is a plus). Good instincts and a passion for API ergonomics: naming, composability, types, error handling, configurability, and clarity. Strong written communication: you can write specs that engineers can implement without ambiguity. Passion for engineering standards, pragmatism, and a bias towards incremental development without compromising long term design. What Modular brings to the table: Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders. World-class Benefits. In order to attract the best, we need to offer the best. Your benefits package may include comprehensive healthcare coverage, retirement and savings programs, employee stock purchase opportunities, paid time off, wellbeing resources, family support programs, and learning and development opportunities. Please note that specific benefit packages may vary based on your location, you can read more about benefits offered by Qualcomm here . Competitive Compensation. We offer very strong compensation packages, including RSU grants. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is The estimated base salary range for this role to be performed in the US, regardless of the state, is $120,000.00 - $222,000.00 USD . The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply, as we may have upcoming openings at lower or higher levels than the one advertised.
Tech Lead, Systems & Platform Applied AI
ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together. We have synthetic pipelines and modular quality control systems that run in unison to generate highest quality tasks and at scale. All of it runs on backend systems that have to stay reliable, fast, and observable while the volume behind them grows every month. As a Tech Lead for the Applied AI Backend Systems, you'll own services in that stack: designing the data models, building the APIs, services, Data pipelines that move work through the platform. This is a build role and you'll take a problem that's roughly scoped, ambiguous, make the design calls, ship it to production, and own it afterward, mentor other engineers on the team and grow them. We're hiring for depth in backend fundamentals rather than any particular domain. If you've built and operated real services, handled the schema migration that couldn't take downtime, found the query that fell over at 10x traffic, designed the retry logic that made a flaky dependency invisible to users, or build a system that recover when things break that's the experience that matters here. You'll work with a talent dense group of engineers who will review your designs and push your thinking. What you will Do Own the architecture of the Applied AI backend domain; core services, data models, orchestration systems and the pipeline execution layer that the product and ops team in the org depends on. Set the technical direction, then stay hands-on enough to build the hardest parts yourself. You'll take problems that arrive undefined, decide what's worth building, and own the outcome - the scoping is part of the job, write the design, ship the code, instrument it, and keep it healthy in production. Build and tune high-throughput data and job pipelines: queuing, batching, idempotency, retries, and backpressure. Make the system fast and reliable by adding failure recovery in pipelines, profile hot spots, Agent token and cost attribution, caching issues, and set latency, error, cost budgets you actually hold to. Own the design review bar for backend work across the org. Mentor senior engineers, make the technical tradeoffs legible to leadership in writing, and raise the standard for how we build. Provision and manage infrastructure as code using Terraform and at scale. Manage and launch 10s of 1000s of containers, sandbox environments, manage resource allocation and system health. Participate in on-call for the systems you own, debug production incidents, and write up what you learn in RCCA. Drive XFN alignment across teams through technical judgment and work directly with product, operations, and research partners to turn ambiguous requirements into systems that ship. What we are Looking For 8+ years of professional backend engineering experience building and operating production systems with a track record of owning architecture across multiple teams and of decisions that aged well. Experience mentoring senior engineers, not just junior ones. Strong fundamentals in backend engineering: data structures, algorithms, concurrency, and writing code that's clear enough for the next person to change. Hands-on experience with API design - REST, gRPC, or GraphQL, and an understanding of versioning, contracts, and backward compatibility. Solid database skills: relational data modeling, indexing, query performance, transactions and isolation, and safe migrations. Familiarity with at least one NoSQL or key-value store and when it's the right choice. Deep, hands-on expertise in distributed systems: queues and event streams, caching, idempotency, rate limiting, and designing for partial failure. Experience with Data Orchestration and workflow management systems like Airflow, Temporal, Dagster. Be able to roll your sleeves up and dig deeper into the lower level infrastructure issues container, permissions, logs, traces and find the needle in the haystack. Experience running services in production: containers, CI/CD, monitoring and alerting, and debugging issues under real traffic. Comfort with ambiguity you can take a loosely defined problem, ask the right questions, and come back with a plan. Strong opinions, loosely held. Genuine excitement for agentic development and new technology, fluency with modern AI dev tools (e.g. Claude Code, Cursor, Copilot), and a real passion for writing good code. Clear written and verbal communication. High ownership, pragmatism, and a bias toward shipping. Nice to Have Experience building or integrating with LLM-backed services in production (evaluation, orchestration, or serving). Familiarity with AI infrastructure providers like Modal, Fireworks, Baseten, Temporal Benefits Bi-annual performance bonus structure Generous equity grant vested over 4 years Up to $15k Relocation bonus $10K housing bonus (if you live within 0.5 miles of our office) $1.5K monthly stipend for meals Free Equinox membership $200 monthly laundry reimbursement $200 monthly personal wellness reimbursement Health, Dental, Vision insurance
Software Engineer, Systems & Platform Applied AI
ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. ABOUT THE ROLE The Applied AI org builds the systems that turn human expertise into training data for frontier models, task pipelines, expert workflows, evaluation infrastructure, and the services that tie them together. We have synthetic pipelines and modular quality control systems that run in unison to generate highest quality tasks and at scale. All of it runs on backend systems that have to stay correct, fast, and observable while the volume behind them grows every month. As a Software Engineer on Backend Systems, you'll own services in that stack: designing the data models, building the APIs, services, data pipelines that move work through the platform. This is a build role. You'll take a problem that's roughly scoped, make the design calls, ship it to production, and own it afterward. We're hiring for depth in backend fundamentals rather than any particular domain. If you've built and operated real services, handled the schema migration that couldn't take downtime, found the query that fell over at 10x traffic, designed the retry logic that made a flaky dependency invisible to users, or build a system that recover when things break that's the experience that matters here. You'll work with a talent dense group of engineers who will review your designs and push your thinking, and you'll be expected to grow into owning larger surfaces quickly. WHAT YOU WILL DO - Design, build, and operate backend services in the Applied AI stack including APIs, data models, background jobs, and the pipelines that connect them. - Own features end to end: scope the problem, write the design, ship the code, instrument it, and keep it healthy in production. - Build and tune high-throughput data and job pipelines: queuing, batching, idempotency, retries, and backpressure. - Make the system fast and reliable by adding failure recovery in pipelines, profile hot spots, Agent token and cost attribution, caching issues, and set latency, error, cost budgets you actually hold to. - Instrument what you ship: observability, metrics, logging, tracing, and alerts that proactively catch problems. - Work on modern cutting edge tools, libraries and frameworks. - Manage and launch 10s of 1000s of containers, sandbox environments, manage resource allocation and system health. - Manage infrastructure as code using Terraform. - Participate in on-call for the systems you own, debug production incidents, and write up what you learn in RCCA. - Write clear design docs and give useful code review, we make technical decisions in writing and expect everyone to take part. - Work directly with product, operations, and research partners to turn ambiguous requirements into systems that ship. WHAT WE ARE LOOKING FOR - 2–5 years of professional backend engineering experience building and operating production systems. - Strong fundamentals in backend engineering: data structures, algorithms, concurrency, and writing code that's clear enough for the next person to change. - Hands-on experience with API design - REST, gRPC, or GraphQL, and an understanding of versioning, contracts, and backward compatibility. - Solid database skills: relational data modeling, indexing, query performance, transactions and isolation, and safe migrations. Familiarity with at least one NoSQL or key-value store and when it's the right choice. - Practical experience with distributed systems basics: queues and event streams, caching, idempotency, rate limiting, and designing for partial failure. - Experience with Data Orchestration and workflow management systems like Airflow, Temporal, Dagster. - Be able to roll your sleeves up and dig deeper into the lower level infrastructure issues container, permissions, logs, traces and find the needle in the haystack. - Experience running services in production: containers, CI/CD, monitoring and alerting, and debugging issues under real traffic. - Comfort with ambiguity you can take a loosely defined problem, ask the right questions, and come back with a plan. - Genuine excitement for agentic development and new technology, fluency with modern AI dev tools (e.g. Claude Code, Cursor, Copilot), and a real passion for writing good code. - Clear written and verbal communication. High ownership, pragmatism, and a bias toward shipping. NICE TO HAVE - Experience building or integrating with LLM-backed services in production (evaluation, orchestration, or serving). - Familiarity with AI infrastructure providers like Modal, Fireworks, Baseten, Temporal BENEFITS - Bi-annual performance bonus structure - Generous equity grant vested over 4 years - Up to $15k Relocation bonus - $10K housing bonus (if you live within 0.5 miles of our office) - $1.5K monthly stipend for meals - Free Equinox membership - $200 monthly laundry reimbursement - $200 monthly personal wellness reimbursement - Health, Dental, Vision insurance
Enterprise Applied AI Leader
ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. About the Role Within Mercor, our Enterprise AI organization builds the infrastructure enterprises need to deploy continuously improving production AI systems. Rather than relying on hand-written prompts and manual workflows, we help organizations translate how their best people work into agent behavior, evaluate outputs against measurable quality standards, and create feedback loops that make agents smarter over time. Our platform combines organizational context, evaluation systems, and quality guardrails into a stack that powers accelerated AI deployment in weeks instead of months. Proven at scale with the world’s leading frontier AI labs, our technology now powers AI deployments across Fortune 500 organizations. This full-time leadership role sits within Applied AI (the Forward Deployed Engineering team of our Enterprise AI organization) and operates separately from Mercor's expert network. We're hiring Applied AI Leads to build and scale the technical delivery team responsible for deploying Mercor's Enterprise AI platform for enterprise customers. This is a highly customer-facing engineering leadership role that is tightly integrated with our Sales/GTM and delivery teams. You’ll lead engineers in the end-to-end technical delivery of production-grade AI systems, working hand-in-hand with customer stakeholders to solve technically complex business problems and contributing to the overall commercial relationship with the customer. Success is measured by customer outcomes and overall commercial impact, not individual code output. You'll own technical delivery, coach engineers, remove blockers, and ensure deployments are reliable, scalable, and customer-ready. You have a deep understanding of customer workflows, use case requirements, and acceptance criteria. While you’re expected to be technically credible and capable of hands-on contribution, your primary responsibility is enabling your engineering team to execute. What You'll Do - Partner directly with customers to align technical requirements with business objectives, acting as the critical bridge between engineering and Sales, GTM, and delivery - Co-lead a Technical team with an Operations counterpart to deliver scalable, production-ready AI systems for enterprise customers - Translate ambiguous workflows into scalable AI-powered solutions, integrating across enterprise systems, APIs, internal tools, and data sources - Guide the deployment of AI workflows, agent orchestration, evaluation systems, and continual learning feedback loops - Hire, mentor, and develop exceptional engineers while establishing rigorous engineering and technical delivery practices as the organization scales - Work closely with Sales/GTM, Product, Research, and Platform Engineering to bring new AI capabilities into production What We're Looking For - Bachelor’s Degree in Computer Science or a related technical degree such as Electrical Engineering, Physics, Mathematics or Statistics - 5+ years building production software systems, with strong software engineering fundamentals in Python, Go, Java, Rust, or similar languages - 2+ years directly managing technical teams - Proven track record leading customer-facing technical delivery for enterprise software, AI products, or developer platforms - Deep experience designing designing distributed systems and cloud-native applications - Highly comfortable communicating complex technical concepts to both engineers and executive-level customer stakeholders - Demonstrated ability to lead through ambiguity, coach others, make decisive technical calls, and maintain high execution velocity in unstructured environments Nice to Haves - AI agents or agent orchestration - LLM applications - Evaluation systems or benchmarking - Enterprise integrations - Workflow automation - Production ML systems Who Thrives Here You enjoy solving ambiguous technical problems with customers, building high-performing teams, and shipping production systems that create measurable business value. You are a technical delivery leader first, and an individual contributor second. Your instinct is to remove blockers, build deep trust with enterprise stakeholders, and partner closely with sales to ensure mutual success. Why Join Mercor - Build production AI systems deployed for some of the world's largest enterprises - Help define how organizations adopt agentic AI at scale - Lead a high-impact, forward-deployed engineering organization from its earliest stages - Work alongside elite engineers, researchers, and operators at the forefront of enterprise Benefits - Participation in the Enterprise revenue sharing pool - Generous equity grant vested over 4 years - Up to $15k Relocation bonus - $10K housing bonus (if you live within 0.5 miles of our office) - $1.5K monthly stipend for meals - Free Equinox membership - $200 monthly laundry reimbursement - $200 monthly personal wellness reimbursement - Health, Dental, Vision insurance
Research Engineer
Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal. ABOUT THE ROLE As a Research Engineer, you’ll work on training, evaluating, and serving large AI models and new inference-time compute techniques, build internet-scale datasets, and help prototype new research and product ideas. WHAT YOU'LL WORK ON - Optimize inference throughput for novel model architectures - Contribute to frameworks used for our research and production workloads - Train trillion-parameter models on large GPU clusters - Curate post-training datasets to improve targeted capabilities - Build out internet-scale data pipelines and crawlers - Design, prototype, and optimize new model architectures - Contribute to research across long-context, inference-time compute, RL, and more WHAT WE’RE LOOKING FOR - Strong general software engineering skills - Thorough knowledge of the deep learning literature - Experience with pre- and post-training of LLMs - Ability to come up with and evaluate research ideas - Experience working with large distributed systems - Ability to handle large ETL workloads OUR CULTURE - Integrity. Words and actions should be aligned - Hands-on. At Magic, everyone is building - Teamwork. We move as one team, not N individuals - Focus. Safely deploy AGI. Everything else is noise - Quality. Magic should feel like magic Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience. COMPENSATION, BENEFITS, AND PERKS (US) - Annual salary ranges between $275K - $550K based on experience - Equity is a significant part of total compensation, in addition to salary - 401(k) plan with 6% salary matching - Generous health, dental and vision insurance for you and your dependents - Unlimited paid time off - Visa sponsorship and relocation stipend to bring you to SF, if possible - A small, fast-paced, highly focused team
Member of Technical Staff, Pre-training Systems
Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal. ABOUT THE ROLE As a Research Engineer on the Pre-training Systems team, you will design and operate the distributed infrastructure that trains Magic’s long-context models at scale. This role focuses on large-scale model training across massive GPU clusters. You will work at the boundary between deep learning and distributed systems, ensuring that training runs are performant, reliable, and reproducible under extreme scale. Magic’s long-context models create non-trivial systems challenges: sustained memory pressure, communication overhead across thousands of devices, long-running jobs that must survive failures, and efficient sequence packing under hardware constraints. You will own the systems that make large-scale pre-training stable and fast. WHAT YOU’LL WORK ON - Scale distributed training across large GPU clusters (data, tensor, pipeline parallelism) - Optimize communication patterns and gradient synchronization - Improve checkpointing, fault tolerance, and job recovery systems - Profile and eliminate performance bottlenecks across compute, networking, and storage - Improve experiment reproducibility and orchestration workflows - Increase hardware utilization and training throughput - Collaborate with Kernels and Research to align model architecture with systems realities WHAT WE’RE LOOKING FOR - Strong software engineering and distributed systems fundamentals - Experience training large models in multi-node GPU environments - Deep understanding of parallelism strategies and performance trade-offs - Experience debugging cross-layer issues in production ML systems - Strong ownership mindset and ability to operate critical infrastructure - Track record of improving performance or reliability of large-scale systems OUR CULTURE - Integrity. Words and actions should be aligned - Hands-on. At Magic, everyone is building - Teamwork. We move as one team, not N individuals - Focus. Safely deploy AGI. Everything else is noise - Quality. Magic should feel like magic Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience. COMPENSATION, BENEFITS, AND PERKS (US): - Annual salary range: $275K - $550K - Equity is a significant part of total compensation, in addition to salary - 401(k) plan with 6% salary matching - Generous health, dental and vision insurance for you and your dependents - Unlimited paid time off - Visa sponsorship and relocation stipend to bring you to SF, if possible - A small, fast-paced, highly focused team
Member of Technical Staff, Inference & RL Systems
Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal. ABOUT THE ROLE As a Research Engineer on the Inference & RL Systems team, you will design and operate the distributed systems that serve our models in production and power large-scale post-training workflows. This role sits at the boundary between model execution and distributed infrastructure. You will work on systems that determine inference latency, throughput, stability, and the reliability of RL and post-training training loops. Magic’s long-context models introduce demanding execution constraints: KV-cache scaling, memory pressure under long sequences, batching trade-offs, long-horizon trajectory rollouts, and sustained throughput under real-world workloads. You will own the infrastructure that makes both production inference and large-scale RL iteration fast and reliable. WHAT YOU’LL WORK ON - Design and scale high-performance inference serving systems - Optimize KV-cache management, batching strategies, and scheduling - Improve throughput and latency for long-context workloads - Build and maintain distributed RL and post-training infrastructure - Improve reliability of rollout, evaluation, and reward pipelines - Automate fault detection and recovery for serving and RL systems - Profile and eliminate performance bottlenecks across GPU, networking, and storage layers - Collaborate with Kernels and Research to align execution systems with model architecture WHAT WE’RE LOOKING FOR - Strong software engineering and distributed systems fundamentals - Experience building or operating large-scale inference or training systems - Deep understanding of GPU execution constraints and memory trade-offs - Experience debugging performance issues in production ML systems - Ability to reason about system-level trade-offs between latency, throughput, and cost - Track record of owning critical production infrastructure OUR CULTURE - Integrity. Words and actions should be aligned - Hands-on. At Magic, everyone is building - Teamwork. We move as one team, not N individuals - Focus. Safely deploy AGI. Everything else is noise - Quality. Magic should feel like magic Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience. COMPENSATION, BENEFITS, AND PERKS (US) - Annual salary range: $275K - $550K - Equity is a significant part of total compensation, in addition to salary - 401(k) plan with 6% salary matching - Generous health, dental and vision insurance for you and your dependents - Unlimited paid time off - Visa sponsorship and relocation stipend to bring you to SF, if possible - A small, fast-paced, highly focused team
Software Engineer, Inference
You'll own how Luma's models get served — integrating new architectures into the inference engine, scaling deployments across thousands of machines, and keeping expensive GPU fleets busy while meeting internal SLOs. This is large-scale inference systems work: scheduling, fleet management, deployment pipelines, and reliability across clusters and hardware providers. It fits a strong systems engineer comfortable with model serving and Kubernetes at scale. If you want pure modeling rather than the systems that run models, this is firmly the systems side. What You'll Own - Ship new model architectures by integrating them into the inference engine. - Collaborate across research, engineering, and infrastructure to optimize model efficiency and deployments. - Build internal tooling to measure, profile, and track the lifetime of inference jobs and workflows. - Automate, test, and maintain inference services for maximum uptime and reliability. - Manage and optimize inference workloads across clusters and hardware providers, and scale deployments across thousands of machines. - Build scheduling systems that use expensive GPU resources optimally while meeting SLOs, and maintain CI/CD for model checkpoints and SDKs. First 90 Days One way the first 90 could unfold. - Days 1–30 — Immerse & Diagnose: Learn the inference stack, the fleets, and where reliability or utilization break. - Days 30–60 — Ship & Validate: Integrate a model or ship tooling/scheduling that improves uptime or GPU utilization. - Days 60–90 — Scale & Systemize: Harden deployment pipelines and scheduling across clusters and providers. What You Bring - Strong Python and system-architecture skills. - Experience deploying models with PyTorch, Hugging Face, vLLM, SGLang, TensorRT-LLM, or similar. - Experience with queues, scheduling, traffic control, and fleet management at scale. - Experience with Linux, Docker, and Kubernetes, and with orchestration, deployment, and scheduling. - Familiarity with Redis and S3-compatible storage. Nice to Have - Modern networking stacks including RDMA (RoCE, InfiniBand, NVLink). - High-performance large-scale ML systems (100+ GPUs). - CUDA, and FFmpeg or multimedia processing. About Luma: Luma's mission is to build unified general intelligence that can generate, understand, and operate in the physical world. We believe multimodality is critical for intelligence — the next step beyond language models comes from vision. Luma is an equal opportunity employer.
Research Engineering Lead
TL;DR - We’re looking for a hands-on research and engineering leader to get the best performance out of commercial and open source frontier models, in order to power the future of AI software engineering. You’ll own experiments end-to-end—from dataset design to model alignment and performance optimization. Must be curious, experimental, and obsessed with squeezing the most out of models.ae WHY LOVABLE? Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we’re just getting started. We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world. Lovable is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software. WHAT WE’RE LOOKING FOR - Led or contributed to cutting-edge LLM research at top AI labs - Fine-tuned large-scale transformer models on datasets including code, natural language, and multimodal inputs` - Developed state-of-the-art models for code generation - Designed high-quality experiments and have strong sense for effective evaluation - A natural leader obsessed with building the best technical team in the world - Mentored team of researchers / engineers, and led collaborative projects across research, engineering, and product teams - Bonus: Published at top ML/AI conferences on LLMs, code intelligence, or agentic reasoning WHAT YOU’LL DO In one sentence: Build the most powerful ensemble of LLMs into lovable products. - Design and execute experiments grounded in real coding and product use cases - Define, track and optimize product-centric LLM performance metrics - Partner with engineering leads to hire and hone a world-class team - Own training pipelines, distillation workflows, and synthetic data generation systems - Work closely with infra and product engineers to scale and ship model improvements OUR TECH STACK We're building with tools that both humans and AI love: - Frontend: React for lightning-fast interfaces - Backend: Golang and Rust for serious performance - Cloud: Cloudflare, Google Cloud Run, AWS, Terraform - DevOps & Tooling: CI/CD pipelines, observability, infra-as-code And always on the lookout for what's next! HOW WE HIRE 1. Fill in a short form then jump on an intro call with the team. 2. Complete the take-home exercise 3. Show us how you approach problems during two technical interviews 4. Join us for trial work lasting 2 days preferably on-site. We'll see how you tick and you get to meet the team and explore whether joining Lovable feels right for you. About your application - Please submit your application in English - it’s our company language so you’ll be speaking lots of it if you join - We treat all candidates equally - if you’re interested please apply through our careers portal
Member of Technical Staff, Infrastructure
Join us and help shape the future of AI by defining the narrative around document understanding. ABOUT THE ROLE The Infra team at LlamaIndex owns the foundations that our product is built upon as well as many of the tools that enable engineers to develop, ship, and observe their code. We are responsible for designing, building, and scaling core infrastructure that powers a high-volume data platform for AI applications. We are looking for team members who love building enabling systems that empower our engineers and power our rapidly growing product. We’re looking for folks with experience managing cloud infrastructure, working through various stages of scale, and helping the broader Engineering team be more effective and productive. Some traits that are important to our company culture: customer-obsessed, collaborative, hard-working, and optimistic. And we’re looking for owners, so we hope you’ll help us expand this list. RESPONSIBILITIES - Collaborate with other engineering teams to build and maintain foundational systems that empower developers and support the company's rapid growth. - Design and implement scalable infrastructure solutions for various deployment models, including SaaS, single-tenant, and private deployments. - Manage and optimize cloud resources and Kubernetes clusters for cost-effectiveness and performance. - Enable external customer deployment success through maintaining clear infrastructure boundaries and principles. - Optimize and improve the release and deployment processes to enhance efficiency and reliability. - Ensure compliance with relevant regulations and implement robust security measures across different deployment environments. - Build and operate infrastructure for production LLM applications, including model integrations, inference workloads, evaluation pipelines, observability, and the reliable execution of agentic workflows. QUALIFICATIONS - 8+ years of engineering experience. - Worked on Platform or Infrastructure teams on significant projects involving infrastructure components (Terraform/CDKTF, Kubernetes, Helm, test infrastructure, release management, observability, etc.) - Experience in optimizing cloud resource utilization. - Proficient in tuning Kubernetes clusters and cloud resources for cost and performance efficiency. - Willing to build LlamaIndex’s engineering culture as we grow. - You can balance speed and pragmatism and build the appropriate solutions for each stage of the company’s growth. - Hands-on proficiency with modern LLM tooling and production AI systems, including experience with model APIs, agent or RAG frameworks, evaluation and tracing tools, and the operational characteristics of LLM workloads. PREFERRED QUALIFICATIONS - Experience building out infrastructure from the ground up at a fast-growing startup. - Experience with observability tools like Prometheus, Grafana, and New Relic. - Experience with GitOps tools like ArgoCD and Flux for continuous deployment. - Experience with security compliance and audits in cloud environments such as SOC2. - Familiar with Python, Postgres, multi-cloud deployments LOCATION We offer a hybrid-friendly culture based out of our downtown San Francisco office. WHY JOIN US? - Impactful Mission: Work on innovative AI products that redefine how knowledge is accessed and utilized. - Collaborative Team: Join a team of passionate individuals committed to pushing the boundaries of technology. - Growth Opportunities: Be at the forefront of the AI revolution, with ample opportunities to grow alongside our scaling organization. ADDITIONAL BENEFITS - Competitive base salary and equity compensation - Comprehensive medical/dental/vision coverage for you and your family - Unlimited paid time off policy - Daily catered lunch and snacks in the San Francisco office Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. LlamaIndex does not accept unsolicited agency resumes. Please do not forward resumes to our jobs alias, employees, or any other organization location. LlamaIndex is not responsible for any fees related to unsolicited resumes.
Member of Technical Staff - Distributed Training E...
ABOUT LIQUID AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there. THE OPPORTUNITY Our Training Infrastructure team is building the distributed systems that power our next-generation Liquid Foundation Models. As we scale, we need to design, implement, and optimize the infrastructure that enables large-scale training. This is a high-ownership training systems role focused on runtime/performance/reliability (not a general platform/SRE role). You’ll work on a small team with fast feedback loops, building critical systems from the ground up rather than inheriting mature infrastructure. WHAT WE'RE LOOKING FOR We need someone who: - Loves distributed systems complexity: Our team builds systems that keeps long training runs stable, debugs training failures across GPU clusters, and improves performance. - Wants to build: We need builders who find satisfaction in robust, fast, reliable infrastructure. - Thrives in ambiguity: Our systems support model architectures that are still evolving. We make decisions with incomplete information and iterate quickly. - Aligns with team priorities and delivers: Our best engineers align with team priorities while pushing back with data when they see problems. THE WORK - Design and build core systems that make large training runs fast and reliable - Build scalable distributed training infrastructure for GPU clusters - Implement and tune parallelism/sharding strategies for evolving architectures - Optimize distributed efficiency (topology-aware collectives, comm/compute overlap, straggler mitigation) - Build data loading systems that eliminate I/O bottlenecks for multimodal datasets - Develop checkpointing mechanisms balancing memory constraints with recovery needs - Create monitoring, profiling, and debugging tools for training stability and performance DESIRED EXPERIENCE Must-have: - Hands-on experience building distributed training infrastructure (PyTorch Distributed DDP/FSDP, DeepSpeed ZeRO, Megatron-LM TP/PP) - Experience diagnosing performance bottlenecks and failure modes (profiling, NCCL/collectives issues, hangs, OOMs, stragglers) - Understanding of hardware accelerators and networking topologies - Experience optimizing data pipelines for ML workloads Nice-to-have: - MoE (Mixture of Experts) training experience - Large-scale distributed training (100+ GPUs) - Open-source contributions to training infrastructure projects WHAT SUCCESS LOOKS LIKE (YEAR ONE) - Training throughput has increased - Overall training efficiency/cost has improved - Training stability has improved (fewer failures, faster recovery) - Data loading bottlenecks are eliminated for multimodal workloads WHAT WE OFFER - Greenfield challenges: Build systems from scratch for novel architectures. High ownership from day one. - Compensation: Competitive base salary with equity in a unicorn-stage company - Health: We pay 100% of medical, dental, and vision premiums for employees and dependents - Financial: 401(k) matching up to 4% of base pay - Time Off: Unlimited PTO plus company-wide Refill Days throughout the year
Technical Program Manager, AI Data
Your Impact at LILA Lila is building toward scientific superintelligence, which depends on a steady supply of high-quality, purpose-built AI data. We're looking for a Senior or Principal Technical Program Manager to join our AI Research team to drive multiple AI data generation and curation workstreams — standing up new project teams, keeping them on schedule, and incorporating that data into the model training pipeline. You don't need to be an ML researcher, but you must be genuinely curious about how AI data fuels model development and able to clearly articulate what your programs will deliver. The successful candidate thrives in ambiguity, communicates exceptionally well across audiences, and knows how to build clarity and momentum on a fast-paced, rapidly scaling team. What You'll Be Building - Launch and operate cross-functional project teams that produce AI data for scientific superintelligence, ensuring each team executes with at high velocity and delivers standardized outputs the model training team can directly consume. - Serve as the key communication interface between project teams and the research, science, and model training organizations; set up the organizational information flows that allow this communication to happen with speed at scale. - Drive accountability across distributed, cross-functional teams without relying on direct authority; build consensus through clear communication and sound judgment. - Define and enforce data delivery standards, QA gates, and handoff protocols so model training receives consistent, high-quality inputs across all active project teams. - Implement best practices for rapid experimentation and iteration, enabling new project teams to ramp efficiently as additional data initiatives come online. - Develop clear documentation and reporting to communicate vision, track progress, and align project team work with broader AI Research priorities; represent program status and risks accurately even when the picture is uncertain or evolving. What You'll Need to Succeed - Bachelor's or Master's degree in Computer Science, Engineering, Life Sciences, or a related field. - 8+ years of program or project management experience in the technology or life sciences field. - Proven experience leading cross-functional programs and driving them to successful completion under tight delivery timelines. - Strong analytical and problem-solving skills, with the ability to turn technical and data requirements into actionable program roadmaps. - Exceptional written and verbal communication skills; track record of producing executive-quality documents, roadmaps, and updates that drive decisions. Bonus Points For - Direct experience in AI/ML research or product organizations, ideally in a program management or research operations capacity. - Working familiarity with model training data pipelines, dataset curation, or ML evaluation workflows — sufficient to engage credibly with researchers and ask good questions. - Experience managing programs that produce standardized outputs for downstream technical consumers (e.g., model training, eval, or platform teams). - Enthusiastic about emerging technologies and experienced in driving rapid experimentation and program iteration. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $192,000 - $272,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Staff Engineer, Data Platform
Your Impact at LILA Lila Sciences is building the software platform that makes automated scientific discovery possible. At the heart of that platform is data: raw outputs from laboratory instruments, experimental model results, curated public datasets, and the scientific literature that contextualizes all of it. The data platform team is responsible for the infrastructure that moves, stores, transforms, and surfaces this data across the organization. We are looking for a Staff Engineer to set the technical direction for our core data infrastructure: ingestion frameworks, storage architecture, orchestration patterns, and the interfaces that let scientists and ML researchers work with data reliably at scale. You will work closely with software engineers, machine learning researchers, and lab scientists to understand requirements and translate them into durable platform capabilities. This is a role for engineers who care deeply about how data systems are designed. You will establish the architectural patterns and engineering standards the broader team builds on, mentor engineers across the data platform group, and make technical decisions that compound over time. What You'll Be Building - Data Platform Architecture: Design and evolve the core data infrastructure that ingests, stores, and serves data across scientific and ML workflows. Make principled build-vs-buy decisions and establish architectural patterns adopted by the broader engineering organization. - Ingestion and Integration: Build reliable pipelines that bring in data from diverse sources: laboratory instruments, public scientific datasets, and external research literature. Own the interfaces between upstream producers and downstream consumers. - Orchestration and Reliability: Operate and extend workflow orchestration systems that run complex, multi-step scientific pipelines. Ensure observability, fault tolerance, and reproducibility across the data stack. - Data Modeling and Schema Strategy: Define and maintain data models, schema evolution practices, and data contracts that ensure consistency, discoverability, and long-term durability of scientific and platform data assets. - Cross-Functional Technical Leadership: Partner with ML researchers, lab scientists, and product engineers to translate scientific and research requirements into platform capabilities. Drive alignment on data standards and integration patterns across teams. - Engineering Standards and Mentorship: Establish coding, review, and design standards for the data platform team. Mentor engineers, lead design reviews, and raise the technical bar across the group. What You’ll Need to Succeed - Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and 8+ years as a software or data engineer with a focus on building and operating data infrastructure. - Designed and shipped data platform components from the ground up, including ingestion frameworks, storage abstractions, and orchestration systems. Fluent in Python and SQL and writes production-quality code. - Production experience with relational and NoSQL databases, schema design, query optimization, and operational concerns at scale. Comfortable working across structured, semi-structured, and unstructured data. - Proven track record of working cross-functionally with scientists, ML researchers, and engineers. Able to translate domain requirements into platform decisions and explain technical trade-offs to diverse audiences. - Experience with cloud infrastructure and containerized deployment (AWS, Kubernetes). - Hands-on experience with modern table formats and open lakehouse patterns (Iceberg, Delta Lake, Hudi). Bonus Points For - Experience with workflow orchestration systems (Flyte, Airflow, Dagster, or similar). - Experience building data infrastructure that serves agentic and LLM-driven workflows, including vector databases, RAG infrastructure, and retrieval-optimized data access patterns. - Background in scientific computing, life sciences, or research software. - Proficiency with AI-assisted development tools (Cursor, Claude Code, or similar) and ability to incorporate them effectively into day-to-day engineering work. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $192,000 - $272,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Research Scientist, Computational Condensed Matter...
Your Impact at LILA Your role will involve applying computational condensed matter physics and electronic structure expertise to accelerate materials discovery, optimization, and understanding. You will use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI systems to investigate complex materials with direct relevance to superconductors, quantum materials, or electronic devices. You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows. The focus is on using computational insight to identify promising materials, explain structure-property relationships, guide optimization, and help agents reason over simulation and experimental data in scientifically grounded ways. This is a hands-on research role for someone who can connect deep condensed matter and electronic structure expertise with practical materials discovery impact. You will collaborate with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations, models, and scientific reasoning into actionable hypotheses and discovery workflows. What You'll Be Building - Apply computational condensed matter physics to materials discovery and optimization. - Use computational physics methods (such as electronic structure and phonon calculations) to study quantum materials, superconductors and electronic devices. - Connect simulation outputs to experimental observations and develop workflows that close the loop between computation and experiment. - Build predictive models from computational and experimental data to guide materials selection and optimization. - Analyze simulation and experimental data to generate actionable materials hypotheses. - Partner with ML, software, and experimental teams on discovery workflows. - Communicate physical insights, model limitations, and recommendations to collaborators. What You'll Need to Succeed - PhD or equivalent experience in Physics, Materials Science, Chemistry, Applied Mathematics, or a related field. - Strong foundation in computational condensed matter physics, electronic structure, or atomistic simulation. - Deep understanding of electronic-structure theory (quantum chemistry, DFT, beyond-DFT methods, etc.) and their application to electronic, magnetic, or quantum materials. - Experience applying first-principles or atomistic methods to materials discovery, optimization, or understanding. - Familiarity with superconductors, quantum materials, electronic materials, semiconductors, or device-relevant materials systems. - Strong programming skills in Python and scientific computing workflows. Bonus Points For - Experience working with amorphous materials, vibrational properties calculations and advanced electronic structure methods. - Experience applying AI/ML to computational materials science or physics-based simulation data. - Familiarity with agentic AI systems, autonomous scientific workflows, or simulation-aware agents. - Background working with quantum materials, superconductors, semiconductors, or electronic device materials. - Experience integrating computational predictions with experimental characterization, device measurements, or closed-loop optimization workflows. - Ability to communicate physical insight, uncertainty, and model limitations to cross-functional collaborators. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $176,000 - $304,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Research Scientist I/II, Computational Organic Ele...
Your Impact at LILA Your role will involve applying computational methods and AI to accelerate the discovery and design of organic electronics materials. You will use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI systems to investigate structure-property relationships in organic and hybrid materials relevant to photovoltaics, semiconductors, optoelectronics, or electronic devices. You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows. The focus is on using computational insight to identify promising materials, explain structure-property relationships, guide optimization, and help agents reason over simulation and experimental data in scientifically grounded ways. This is a hands-on research role for someone who can connect deep organic electronics and computational materials expertise with practical impact for customer-facing scientific programs. You will collaborate with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations, models, and scientific reasoning into actionable hypotheses and discovery workflows. What You'll Be Building - Apply computational modeling and AI for materials discovery and design of organic semiconductors, photovoltaic materials, molecular and polymeric electronic materials, and organic electronic devices. - Model charge transport, excited-state behavior, morphology-property relationships, and other fundamental mechanisms that influence organic electronic device performance. - Connect simulation outputs to experimental observations and develop workflows that close the loop between computation and experiment. - Build predictive models from computational and experimental data to guide materials selection and optimization. - Analyze simulation and experimental data to generate actionable materials hypotheses. - Partner with ML, software, and experimental teams on discovery workflows. - Communicate physical insights, model limitations, and recommendations to collaborators. What You'll Need to Succeed - PhD or equivalent experience in Materials Science, Chemistry, Chemical Engineering, Mechanical Engineering, Physics, or a related field. - Strong foundation in computational materials science and chemistry, including electronic structure methods and large-scale atomistic simulations. - Deep understanding of organic semiconductors, organic electronics, photovoltaics, optoelectronic materials, charge transport, or related device-relevant materials systems. - Experience applying first-principles, molecular simulations, or general atomistic methods to materials discovery, optimization, or understanding. - Ability to connect molecular, morphological, and electronic structure features to device-relevant properties. - Strong programming skills in Python and scientific computing workflows. Bonus Points For - Experience studying organic photovoltaics, organic semiconductors, polymer electronics, molecular electronics, perovskite-organic interfaces, or related materials systems. - Experience applying AI/ML to computational materials science, molecular simulations, or other physics-based simulations. - Strong familiarity with agentic AI systems, autonomous scientific workflows, or simulation-aware agents. - Experience integrating computational predictions with experimental characterization, device measurements, or closed-loop optimization workflows. - Familiarity with charge transport modeling, excited-state calculations, morphology generation, coarse-graining, and/or multiscale and multiphysics simulations. - Ability to communicate physical insight, uncertainty, and model limitations to cross-functional collaborators. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $176,000 - $304,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Senior Product Manager, AI Infrastructure
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. Who We're Looking For We’re looking for a Product Manager, AI Infrastructure to own the product experience for Lightning AI’s GPU cloud, from capacity and provisioning through workload execution, reliability, observability, and customer consumption. This role sits at the intersection of AI infrastructure, cloud platforms, and developer experience. You’ll define how customers discover, provision, configure, and operate GPU compute, while partnering closely with infrastructure engineering and operations to make the platform more reliable, efficient, and scalable. The right candidate understands that infrastructure itself is the product. You should be comfortable reasoning about GPU availability and utilization, cluster provisioning, networking and storage, scheduling and orchestration, workload reliability, and the APIs and workflows that expose these systems to customers. You’ll work across Engineering, Infrastructure, Sales, customers, and the executive team to determine what we build, how infrastructure capabilities are exposed and packaged, and where Lightning AI can differentiate from hyperscalers and other GPU clouds. This is a high-ownership role. You’ll investigate infrastructure and customer problems directly, use data to understand reliability and utilization, make technical tradeoffs with engineers, and drive products from problem definition through launch, adoption, and iteration. You’ll join the Product team and report to our VP of Product. This is a hybrid role based in New York City or San Francisco, with an in-office expectation of two days per week. What You’ll Do - Own the product vision and roadmap for Lightning AI’s GPU cloud infrastructure. - Define how customers discover, provision, configure, and consume GPU compute. - Build product experiences around GPU capacity, clusters, scheduling, networking, storage, and workload execution. - Partner closely with infrastructure and platform engineering to improve availability, reliability, utilization, and performance. - Develop a deep understanding of customer workloads, from experimentation and training through inference, and translate those needs into infrastructure capabilities. - Use infrastructure and product data to identify capacity constraints, reliability issues, performance bottlenecks, and opportunities to improve the customer experience. - Define the APIs, interfaces, and developer workflows through which customers interact with infrastructure. - Make product tradeoffs across customer experience, infrastructure efficiency, reliability, cost, and engineering complexity. - Own pricing, packaging, and consumption models in partnership with Ops, Sales, and Finance. - Partner with GTM on positioning, technical sales conversations, customer feedback, and competitive differentiation. - Define and track metrics across GPU utilization, provisioning, workload reliability, infrastructure consumption, adoption, and retention. - Take products from problem discovery through requirements, launch, adoption, and iteration. What You’ll Need - 7+ years of product management experience, including 3+ years building cloud infrastructure, compute, platform, developer tooling, or AI infrastructure products. - Experience building technical products for developers, infrastructure teams, ML engineers, AI researchers, or other technical users. - Strong understanding of cloud infrastructure concepts including compute, networking, storage, provisioning, scheduling, and orchestration. - Familiarity with GPU infrastructure and the requirements of large-scale AI training, experimentation, or inference workloads. - Technical depth to work directly with engineers on APIs, distributed systems, Kubernetes, workload orchestration, observability, and infrastructure reliability. - Experience using data to understand infrastructure utilization, capacity, reliability, performance, and customer behavior. - Track record of owning technical products from problem definition through launch and adoption. - Strong product judgment and ability to turn complex infrastructure capabilities into simple customer experiences. - Experience with pricing, packaging, consumption-based products, or cloud infrastructure unit economics. - Strong prioritization skills and comfort making tradeoffs across customer needs, reliability, infrastructure efficiency, and engineering investment. - Strong written and verbal communication across technical, customer, and executive audiences. - Comfortable moving quickly and operating in ambiguous environments. - BS in Computer Science, Engineering, or equivalent practical experience. Bonus Points - Experience at a GPU cloud, neocloud, hyperscaler, AI infrastructure company, or infrastructure developer-tools company. - Experience building products involving GPU provisioning, cluster management, capacity management, workload scheduling, or distributed compute. - Familiarity with GPUs, Kubernetes, Slurm, Ray, PyTorch, distributed training, or similar infrastructure technologies. - Experience with reserved capacity, on-demand compute, utilization optimization, or other cloud consumption models. - Experience building infrastructure products that support large-scale AI training and inference. - Experience working closely with data center, hardware, networking, or infrastructure operations teams. We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $200,000 - $250,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Platform Engineer (Forward Deployment)
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. What We Are Looking For We are seeking an experienced Platform Engineer to partner directly with Lightning customers to architect, build, and deploy production AI systems. Working alongside customer engineering teams, you'll solve complex technical challenges across inference infrastructure, distributed systems, APIs, and AI workflows—building reliable, observable systems that perform at scale. You'll translate customer requirements into production-ready software, turn bespoke solutions into reusable platform capabilities, and help shape the evolution of the Lightning Platform. We're looking for a highly technical, customer-oriented platform engineer who thrives in fast-moving, ambiguous environments where success requires deep software engineering expertise, sound systems thinking, and the ability to collaborate directly with customer engineering teams to bring complex AI applications into production. This role is based in one of our hubs (New York City, San Francisco, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. What You'll Do - Partner directly with customers to design, implement, and deploy end-to-end AI systems and workflows on Lightning’s platform - Translate vague customer objectives into clear technical specifications, proof-of-concepts, and scalable production implementations - Own customer technical engagements end-to-end, from early discovery and architecture through deployment, monitoring, and expansion - Develop and maintain production-grade software systems and services using modern programming languages, with a strong preference for Python - Build reliable, observable systems with strong attention to latency, throughput, quality, scalability, and cost efficiency in production environments - Debug and optimize AI systems across inference infrastructure, model behavior, APIs, and distributed workloads to improve performance and reliability - Work closely with customer engineering teams throughout the full lifecycle of AI deployments, including technical discovery, implementation, deployment, and scaling - Collaborate cross-functionally with Lightning’s product and engineering teams to improve platform capabilities, influence roadmap priorities, and identify opportunities for reusable product improvements - Navigate ambiguity with sound technical judgment, making thoughtful tradeoffs and selecting the right tools and approaches without introducing unnecessary complexity - Demonstrate strong ownership and accountability in execution, with a commitment to delivering high-quality outcomes for both customers and internal teams What You’ll Need Required Qualifications - Strong software engineering experience building production full-stack applications, including modern frontend frameworks such as React and TypeScript, and backend services in Python, Go, or similar programming languages. - Experience working directly with customers in highly technical environments, such as Forward Deployed Engineering, Solutions Engineering, Applied AI Engineering, Technical Product Engineering, or related roles - Familiarity with AI/ML pipelines and the lifecycle of model development, evaluation, deployment, and monitoring - Experience deploying and operating production AI/ML systems in cloud or distributed environments - Familiarity with modern AI infrastructure and tooling such as Docker, Kubernetes, APIs, model serving systems, or distributed inference workloads - Strong communication and collaboration skills, especially when working through complex technical topics with customers, engineers, and cross-functional stakeholders - Ability to translate business needs into technical solutions and drive projects from initial concept through production delivery - Ability to execute effectively in ambiguous, fast-moving, high-growth environments - Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field Nice-to-Haves - Experience building, deploying, or optimizing large-scale AI/ML systems in production environments - Experience with modern AI stacks and tooling such as vLLM, TensorRT, Ray, LangGraph, vector databases, or workflow orchestration systems - Familiarity with inference optimization, distributed systems, or GPU-accelerated workloads - Startup experience or experience operating in highly cross-functional environments - Track record of rapidly shipping proof-of-concepts and production systems while maintaining strong engineering quality - Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, AI, or a related technical field Compensation We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $180,000 - $250,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Data Scientist
Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: - Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. - Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. - Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. - Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. - Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. - Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. About the Role We are looking for a Data Scientist to drive informed decision-making across the company as we become the first fully-integrated neocloud for AI training. This individual will work closely with Product, Engineering, and Sales leadership, answering key questions about product usage, proactively surfacing trends, and supporting our growth in a data-driven way. You will join the Product Team and report to our VP of Product. This is a hybrid role based in New York City, NY with in-office requirements of 2 days per week. What You’ll Do - Partner with Product, Sales, and Engineering to define questions that matter and identify product features and behaviors that drive business outcomes - Analyze small business and enterprise usage patterns to sharpen Ideal Customer Profiles and guide Sales prospecting priorities - Quantify the health of our data center business and test the impact of systematic sales, service, and operations improvements - Work with engineering to design, build, and maintain data pipelines that support timely and accurate analyses - Write SQL (and occasional scripts) to explore data, automate recurring workflows, and answer ad-hoc questions - Design Looker and Data Studio dashboards and reports that make findings easy for stakeholders to act on - Monitor trends and surface opportunities or risks early, before they show up in routine reporting - Help grow a data-driven culture by sharing practices and enabling teams to use analytics tools on their own What You’ll Need - 5+ years in a Data Science or Product Analyst role - Proficient using SQL to query large databases - Strong skills using Python to write scripts and run statistical analysis - Hands-on experience with BI tools (Looker or similar) and cloud data infrastructure — AWS (e.g. S3, EFS) and/or GCP (e.g. BigQuery, Looker Studio) - A strong bias for action, and the ability to make clear decisions and recommendations in the presence of uncertainty - Experience on a growing data team at a startup, preferred - Experience designing and building foundational data models from scratch, preferred We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $160,000 - $245,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success: - Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents. - Meaningful Equity: RSUs that give employees a stake in the company's long-term success. - Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.). - Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance. - Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge. - Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments. - Professional Development: Annual learning and development allowance to support your professional growth. - Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being. - Sabbatical Program: Four weeks of paid sabbatical leave after four years of service. - Flexible Work: Flexible schedules and a hybrid work model for our office-based teams. - In-Office Meals: Complimentary meals at our office hubs. Benefits may vary by location, team, and role. At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.
Forward Deployed AI Engineer
Forward Deployed AI Engineer THE OPPORTUNITY We are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering. You will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams. WHO WE ARE At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology. Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites. We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission. WHO YOU ARE - You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks. - You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models. - You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work. - You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures. - You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations. - You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements. WHAT SETS YOU APART - You have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling. - You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features. - You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system. - You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations. YOUR RESPONSIBILITIES Customer deployment & integration: - Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure. - Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements. - Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions. - Ensure deployments meet enterprise standards for security, performance and reliability. Customer advocacy & product feedback: - Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as needed - Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams. - Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings. - Create technical documentation, integration guides and best-practice resources for customers. Self development: - Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling. - Gain a strong working understanding of protein and cell biology as it relates to our product. - Participate in knowledge sharing, e.g. organise and present at our internal reading group. APPLY We offer strongly competitive compensation and benefits packages, including: - Private health insurance - Pension contributions - Generous leave policies (including gender neutral parental leave) - Hybrid working - Travel opportunities and more We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models. We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
Staff Software Engineer - Managed Kubernetes
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. ABOUT THE ROLE Lambda is building the AI Cloud of the future. We are seeking a Staff Engineer to help our development of our Managed Kubernetes platform. Think GKE, but purpose-built for AI workloads and running on bare metal. This is a foundational technical leadership role where you will shape the infrastructure that powers the next generation of AI training and inference at scale. As a Staff Engineer on our Orchestration team, you will collaborate to help drive the technical vision for Lambda's managed orchestration services, including Managed Kubernetes, Managed Slurm on Kubernetes, and higher-level platform services for inference and AIOps. You'll work at the intersection of distributed systems, GPU-accelerated computing, and Cloud Native infrastructure to build systems that are reliable, performant, and elegantly simple for our customers. This is not a role for someone who just operates Kubernetes; it is a technical leadership role for an engineer who has synthesized the core domains of infrastructure (compute, network, storage, security) and can design holistic solutions across all of them. You'll be working closely with NVIDIA's open-source ecosystem, and partnering with internal teams across the stack to deliver a world-class managed platform. WHAT YOU'LL DO PRODUCT ENGINEERING - Drive technical vision for Lambda's Managed Kubernetes bare-metal platform, including control plane scalability, multi-tenancy, cluster lifecycle management, and high availability - Integrate and extend NVIDIA's open-source ecosystem: GPU Operator, Network Operator, DCGM, NCCL, and emerging projects like AICR and Topograph for topology-aware scheduling and placement - Design GPU-aware orchestration systems - Lead development of services that power our managed services - Inform on and help with networking solutions for AI workloads: CNI integration (Cilium, Multus), high-performance fabrics (InfiniBand, RoCE), RDMA, and GPUDirect. You will work closely with our Network team to define and drive requirements - Inform and help with storage architecture requirements for AI workloads. You will partner with Storage teams on what managed K8s, Slurm, and future services need - Build the foundation for Managed Slurm on Kubernetes, enabling traditional HPC workloads to run seamlessly alongside Kubernetes workload - Design higher-level platform services for inference, including model serving infrastructure, autoscaling based on inference load, and multi-model deployment patterns - Design self-healing systems and automation for incident response, root cause analysis, and platform resilience - Lead chaos engineering efforts to validate system behavior under failure conditions at scale - Establish operational excellence for a managed service: upgrade automation, security patching, and zero-downtime maintenance CROSS-FUNCTIONAL INFRASTRUCTURE LEADERSHIP - Serve as the technical bridge between Orchestration and other infrastructure teams (Network, Storage, Security), translating platform requirements into actionable specifications - Drive infrastructure-wide decisions that enable successful managed services. You’re someone who understands what's needed end-to-end, not just at the Kubernetes layer. - Provide input on bare-metal provisioning, network topology, and storage systems to ensure they meet the needs of managed the services being built by the Orchestration organization - Champion consistency and standardization across Lambda's infrastructure stack - Work directly with customers and internal teams to understand existing deployments and chart a path to the managed platform TECHNICAL LEADERSHIP - Set technical direction for Kubernetes services across the Orchestration team, influencing roadmap and prioritization - Drive reviews and design sessions, ensuring we build systems that are scalable, maintainable, and aligned with customer needs - Mentor and grow engineers, establishing best practices for Kubernetes development, distributed systems, and Cloud Native engineering - Collaborate cross-functionally with Network, Storage, Security, and Customer Success teams - Engage with NVIDIA and the open-source community to stay current on GPU orchestration technologies and contribute back where appropriate - Represent Lambda externally through technical blog posts, conference talks, and strategic customer engagements - Shape our AIOps vision: design intelligent systems for automated capacity planning, anomaly detection, and predictive maintenance of cloud infrastructure WHO YOU ARE You are a creative, innovative engineer who operates at high velocity. You don't just solve problems. You find elegant solutions and ship them quickly. You embrace modern tools and AI-assisted development (like Claude Code) to accelerate your productivity and multiply your impact. You're energized by building new things, not maintaining the status quo. REQUIRED QUALIFICATIONS - 10+ years of experience in software engineering, platform engineering, or SRE, with at least 5 years focused on Kubernetes at scale - Expert-level understanding of Kubernetes internals: API machinery, controllers, schedulers, operators, CRDs, CSI, CNI, and the extension patterns that make Kubernetes powerful - Holistic infrastructure expertise: you've synthesized knowledge across compute, networking, storage, and security, not just Kubernetes in isolation. You can build solutions that span the full stack. - Strong software engineering skills in Go (required) and Python; you write production-quality code, not just scripts - Deep experience with GPU orchestration in Kubernetes: NVIDIA GPU Operator, device plugins, DCGM, MIG, time-slicing, and GPU-aware scheduling. Familiarity with NVIDIA Network Operator and GPUDirect is strongly preferred. - Proven track record of technical leadership: driving design decisions across teams, mentoring engineers, and influencing infrastructure direction beyond your immediate scope - Deep experience designing and operating managed services or multi-tenant platforms. You understand what it takes to run infrastructure for external customers - Strong understanding of distributed systems principles: consensus, fault tolerance, consistency models, and graceful degradation - Experience with observability at scale: Prometheus, Grafana, distributed tracing, and building actionable alerting systems - Solid knowledge of Linux systems and networking (L2-L7), including high-performance networking concepts (RDMA, InfiniBand, RoCE) - Experience with infrastructure-as-code and GitOps workflows PREFERRED QUALIFICATIONS - Experience building and operating managed Kubernetes services (GKE, EKS, AKS, or similar) or working on Kubernetes control plane components - Hands-on experience with NVIDIA's open-source ecosystem beyond GPU Operator: Network Operator, NCCL tuning, Topograph, AICR, or similar emerging projects - Familiarity with HPC and traditional job schedulers (Slurm) and Kubernetes-native batch scheduling (KAI, Volcano, Kueue) - Background in confidential computing - Experience migrating customers or workloads from legacy/bespoke infrastructure to standardized platforms - Contributions to CNCF projects, Kubernetes SIGs, or NVIDIA open-source projects - Familiarity with security and compliance in multi-tenant environments: RBAC, Pod Security Standards, network policies, workload isolation - Background in ML infrastructure: training clusters, inference serving, simulation WHY LAMBDA Lambda is building the essential infrastructure for the AI era. We're not just another cloud provider: we're a company founded by ML practitioners, for ML practitioners. Our customers include leading AI research labs and enterprises pushing the boundaries of what's possible with artificial intelligence. What makes this role special: - You'll be building core platform services the world’s largest AI companies will consume - NVIDIA partnership: Deep integration with NVIDIA's GPU and networking stack, working with cutting-edge open-source tooling - Real technical challenges: Massive scale GPU clusters and the unique demands of AI workloads - Cross-stack influence: Shape not just Kubernetes, but the network, storage, and compute infrastructure that supports it - Direct impact: Your work enables AI breakthroughs. Every model trained on Lambda benefits from systems you build - World-class team: Work alongside engineers with deep expertise in ML, systems, and infrastructure Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG - Our values are publicly available: https://lambda.ai/careers - We offer generous cash & equity compensation - Health, dental, and vision coverage for you and your dependents - Wellness and commuter stipends for select roles - 401k Plan with 2% company match (USA employees) - Flexible paid time off plan that we all actually use Equal Opportunity Employer Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Account CTO
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance. What You’ll Do - Strategic Technology Leadership for Key Accounts - Serve as the primary technical liaison for Lambda's strategic Superintelligence accounts - Cultivate and sustain executive level technical relationships, establishing Lambda as a trusted technology partner and strategic advisor - Drive multi-year technology roadmaps aligned with customer business objectives and Lambda's product portfolio - Influence customer technology strategy and adoption at the executive level - Represent Lambda at executive briefings, board meetings, and strategic planning sessions - Own Technical Strategy and Business Outcomes - Partner with Global Account teams to drive strategic account growth and expansion - Lead architectural reviews and technology assessments at the enterprise level - Define and articulate business value propositions, ROI models, and TCO analyses for executive stakeholders - Orchestrate cross-functional teams including Solutions Engineers, Forward Deployed Engineers, Professional Services, and Product Management - Own technical escalations and serve as the Executive Technical Sponsor for critical customer initiatives - Drive adoption of Lambda's strategic initiatives within key accounts - Technology Vision and Thought Leadership - Establish yourself as a trusted advisor on AI/ML transformation and cloud strategy - Guide customers through digital transformation journeys and emerging technology adoption - Publish thought leadership content, speak at industry events, and represent Lambda in executive forums - Influence Lambda's product strategy based on strategic customer needs and market trends - Mentor and develop technical talent across the organization You - Have 15+ years of experience designing, deploying and scaling cloud infrastructure - Have 6+ years of experience working directly with C-suite executives and senior leadership teams in advisory or consultative capacities - Have 5+ years driving cloud transformation initiatives at enterprise scale - Have proven track record of influencing C-suite executives and board-level stakeholders - Have deep expertise in AI/ML technologies and their business applications - Have experience with NVIDIA DGX/HGX/MGX systems, InfiniBand &RoCE networking, and large-scale GPU cluster deployments - Have experience with storage architectures including distributed file systems, object storage, high-performance parallel file systems, and NVMe-based solutions - Have hands-on experience with LLM training, fine-tuning, and inference at scale - Have experience with enterprise architecture frameworks and governance models - Have experience managing or influencing deals worth $1B+ annually - Have strong business acumen with ability to translate technology into business outcomes - Have experience navigating complex organizational dynamics and driving consensus - Have track record of building strategic partnerships and alliances - Excel at executive communication, presentation, and storytelling - Demonstrate thought leadership through publications, speaking engagements, or industry recognition Nice to Have - MBA or advanced degree in Computer Science, Engineering, or related technical field - Experience as a CTO, VP of Engineering, Chief Architect, or Technical Fellow at a technology company with $100M+ revenue - Track record working with AI labs, research institutions, or frontier model companies - Board advisory experience for technology companies - Published peer-reviewed research, whitepapers, or patents specifically in distributed computing, GPU acceleration, or large-scale ML training infrastructure Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG - Our values are publicly available: https://lambda.ai/careers - We offer generous cash & equity compensation - Health, dental, and vision coverage for you and your dependents - Wellness and commuter stipends for select roles - 401k Plan with 2% company match (USA employees) - Flexible paid time off plan that we all actually use Equal Opportunity Employer Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
Security Engineering Manager, London or Lausanne
Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery. Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you. About Iso Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI. Your impact As Security Engineering Manager at Isomorphic Labs, you will build, scale, and lead a high-performing engineering team at the absolute frontier of Artificial Intelligence and Cybersecurity. Reporting directly to the CISO, you will own the technical security roadmap for our pioneering digital biology platform. This role demands a rare blend of deep technical mastery, sharp business acumen, and people leadership. You will lead from the front, translating complex scientific and business objectives into an actionable, enterprise-grade engineering reality. Operating within a high-growth scale-up environment backed by the Alphabet ecosystem, you will pioneer a robust, AI-first security architecture while remaining a velocity enabler for world-class ML researchers and drug discovery teams. What you will do - Team Leadership: Mentor and scale a world-class team of security engineers, fostering a culture of technical excellence, continuous learning, and high-impact delivery. - Technical Roadmap Ownership: Co-design and implement the long-term technical security strategy covering IAM, Cloud and Network Security, Secure SDLC, Security Monitoring, etc. - Lead Key Transformation Projects: Lead unique, industry-pioneering technical projects that support the development of frontier ML models and new therapeutics. - Cloud & Platform Security through AI: Oversee the security of our cloud infrastructure and platform leveraging AI and agentic workflows, enabling data-driven and automated security posture management. - Program Oversight: In collaboration with the InfoSec TPM and other Engineering leads, develop and maintain a KPI-driven roadmap and provide regular updates to executive management. - Business Velocity: Partner with medical teams and ML researchers to maximize velocity, removing obstacles while maintaining secure compute environments. - Google Collaboration: Act as a key technical liaison within the broader Alphabet/Google ecosystem and with strategic security vendors, ensuring Isomorphic Labs maintains its agile, pioneering edge. - Vulnerability and Incident Escalation: Serve as the senior technical escalation point for complex security incidents, systemic architectural vulnerabilities, and high-stakes risk remediations. Skills and qualifications Essential: - Engineering Leadership: Proven track record of managing, building, or leading technical security teams within fast-paced scale-ups, hyper-growth startups, and/or world-class technology organizations - Strategic Architecture: Deep experience defining, implementing, and defending security architectures across complex, multi-tenant cloud systems. - Industry Exposure: Solid professional exposure to the unique security, regulatory requirements, and architectural challenges found within AI/ML and/or the life sciences industry. - Detail-oriented: The ability to pivot from strategic risk planning to direct, collaborative implementation assistance, and to arbitrate deeply technical trade-offs. - AI and Automation: A bias for automation, scalability, and systematic acceleration through the use of AI and agentic workflows. - Advanced Cloud Engineering: Strong engineering background in securing cloud platforms (GCP preferred), containerized workloads (Kubernetes/Docker), and deploying robust Zero Trust frameworks. - Acute Business & Risk Acumen: Exceptional ability to evaluate security through a commercial and scientific lens, making calculated, data-driven trade-offs that support business agility without compromising core assets. - Translational Communication: Excellent soft skills with a proven ability to distill deep technical vulnerabilities and complex architectural risks into clear, concise, and actionable strategic plans for senior executive leadership and non-security stakeholders. Nice to have: - AI/ML Pipeline & LLM Familiarity: Hands-on experience or deep architectural familiarity with securing ML training lifecycles, protecting proprietary model weights, or building guardrails for autonomous workflows. - Regulated Data & Compliance Mastery: Experience navigating security frameworks (ISO 27001, ISO 42001) or strict data privacy and validation standards common in health tech or pharma (GxP, FDA, EU AI Act). - Advanced Coding & DevSecOps Mastery: Proficiency in Python or Go, alongside deep expertise in automated CI/CD security tooling, Terraform, and advanced cloud-native security controls. - Industry-Recognized Credentials: Professional-level cloud security certifications or technical credentials (e.g., CISSP, CISM, OSCP). Culture and values We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it. Thoughtful Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day. Brave Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. Determined Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we. Together Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere. Creating an extraordinary company We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. Hybrid working It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call. Please note that when you submit an application, your data will be processed in line with our privacy policy . >> Click to view other open roles at Isomorphic Labs
Full Stack Software Engineer, Lab Platform (LIMS)
THE OPPORTUNITY insitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human™ platform identifies novel, high-impact genetic intervention points, which our TherML™ platform translates into therapeutics—whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point. To enable that mission, we need a software layer that ties together the scientific, automation, and machine learning platforms — that's our Lab Platform: a harness for science, built as an agentic workflow system that lets scientists drive the lab through an agent. Our bar is that everything in the lab should be agentically accessible (any action a scientist can take, an agent can take), agentically legible (agents understand what the data means in insitro's context, not just how to fetch it), and humanly verifiable (a scientist can always check what an agent did and why). This is real robotics, workflow automation, and applied agent tooling — and your users are in the building with you. You'll work across the stack — front end, backend, and the integrations that reach into instruments, Benchling, and agent runtimes — partnering closely with our machine learning, automation, and biology teams. Based in South San Francisco, this role reports directly to Senior Manager, Software Engineering and offers an in-person hybrid schedule of three days per week. We'll bring you up to speed in the domain of drug development and back your ideas with real trust and mentorship along the way. RESPONSIBILITIES Full-Stack Ownership - Ship Across the Stack: Build the React and TypeScript frontends scientists use every day, the Python services behind them, and integrations that reach instruments, Benchling, and agent runtimes - Own It End to End: Take a feature from the first conversation with a scientist through the data model and UI to the alert that fires when it breaks - Do the Normal SWE Things: Write code, review design docs, talk to users, and do code reviews that actually make the codebase better Agentic Tooling & Experimentation - Chase User Appreciation: Ship things that make scientists say "OMG, this is amazing, thank you so much." - Figure Out What's Actually Useful: Test agentic tooling ideas through prototypes, real users, and short iterative loops rather than betting on theory - Move the Needle: Contribute work that meaningfully advances insitro's mission and the pace of drug development Cross-Functional Partnership - Go Watch the Work: Spend time in the lab observing the workflow before you change it - Partner Broadly: Collaborate closely with machine learning, automation, and biology teams to build tools people actually use - Keep Humans in the Loop: Design for provenance and verifiability, so a scientist can always check what an agent did and why ABOUT YOU Experience & Qualifications - Tenure: 2–4+ years of experience as a professional software engineer - Engineering Fundamentals: Working knowledge of AWS or GCP, relational databases, and standard practices like version control and code review Core Competencies - Product Instinct: You think like a product person — you want to know who the user is, what they're actually trying to do, and you have opinions about what to build - Curious About the Science: You don't need a biology background, but you want to learn the domain rather than treat it as someone else's problem - Comfortable in the Gray Area: You can reason clearly about the tradeoffs between quality and speed - Fits the Team: You're up for writing design docs, having opinions in code review, and yes, goofing around on Slack. Preferred Qualifications - Domain Experience: Experience with LIMS, lab automation, or another life sciences domain - Agent/LLM Experience: Experience building with LLMs or agent frameworks — tool and skill design, evaluation, or getting a model to behave reliably against real systems - Stack Familiarity: Experience with Django, FastAPI, SQLAlchemy, React, TypeScript, PostgreSQL, Docker, or AWS COMPENSATION & BENEFITS AT INSITRO Our target starting salary for successful US-based applicants for this role is $111,000 - $140,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: - 401(k) plan with employer matching for contributions - Excellent medical, dental, and vision coverage as well as mental health and well-being support - Open, flexible vacation policy - Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc) - Quarterly budget for books and online courses for self-development - New hire stipend for home office setup - Monthly cell phone & internet stipend - Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid - Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process. #LI-Hybrid Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com http://insitro.com, and if in doubt, contact us at info@insitro.com. About insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com http://www.insitro.com.
AI Full Stack Engineer
Help Build the Future of Healthcare AI Infinitus is AI communications in service of patients. Healthcare is inherently complex and siloed. We’re pioneering agentic communications to connect the entire system — any stakeholder, any channel, inbound and out. The result is intelligent care that reduces patient anxiety, increases speed to treatment, and enables teams to scale impact without stretching resources. Our system combines industry-leading safety guardrails with the largest dynamic knowledge graph built on millions of real-world interactions. It’s why 44% of the healthcare Fortune 50 trusts Infinitus to turn fragmented touchpoints into seamless care for better patient outcomes. The Mission At Infinitus, our mission is simple: create time for healthcare by making access, adherence, and affordability easier than ever. We’ve automated over 7 million calls and 100M+ minutes of conversation — saving millions of hours for patients and providers. Backed by over $100M from top investors including Google Ventures, Kleiner Perkins, Andreessen Horowitz, and Coatue, we’re a team that challenges the status quo and moves fast at the intersection of AI and healthcare. Infinitus was recently named to Fast Company's World's Most Innovative Companies and Business Insider’s top startups in healthcare. YOUR ROLE We are looking for a senior Fullstack Software Engineer to help us design, build, and scale the core of our digital health platform. You’ll work on expanding the capabilities of Eva, our AI-powered health assistant, and build systems that automate and simplify healthcare administration at scale. This role blends hands-on backend development with opportunities to lead and influence technical direction and mentor teammates. YOUR IMPACT - Design, build, and scale AI-powered, user-facing products that make Eva’s healthcare interactions more intelligent, intuitive, and reliable. - Lead the end-to-end delivery of complex full-stack product experiences, from frontend architecture and backend services to APIs, data integrations, and production workflows. - Partner closely with Product, Design, Data Science, Infrastructure, and other engineering teams to bring AI capabilities into real user workflows in a practical, scalable, and measurable way. - Translate ambiguous product and AI opportunities into clear technical plans, balancing speed, user experience, reliability, safety, and long-term maintainability. - Build robust systems that connect application logic, data pipelines, model outputs, and human-centered product experiences. - Evaluate and integrate AI technologies, including LLM-enabled workflows, retrieval systems, classification, summarization, automation, and decision-support experiences where appropriate. - Establish strong frontend and backend engineering standards, including component architecture, API design, system reliability, observability, testing, and development best practices. - Make high-quality technical tradeoffs across product impact, engineering complexity, scalability, and long-term platform health. - Drive cross-team and cross-org alignment to ship high-impact work, influencing through technical clarity, judgment, and collaboration rather than authority. - Mentor and grow engineers across the team, raising the bar for technical execution, product thinking, and engineering culture. - Contribute to both short- and long-term technical roadmaps, especially around AI-enabled product development, platform scalability, and full-stack architecture. - Help shape how Eva responsibly applies AI in healthcare workflows, with a focus on usefulness, trust, reliability, and excellent user experience. YOUR SKILLSET - 8+ years of practical full-stack engineering experience - A track record of leading the design and delivery of complex consumer or B2B user-facing products across the full stack. - Deep expertise in modern frontend and backend development, with strong proficiency in technologies such as React, TypeScript, Python, Go, Java, C++, or similar. - Strong experience designing scalable APIs, backend services, data models, integrations, and distributed systems. - Hands-on experience with cloud infrastructure and modern DevOps practices, ideally across AWS, GCP, or similar environments. - Solid understanding of database technologies, including SQL and NoSQL systems, with experience optimizing for performance, reliability, and scale. - Practical familiarity with AI-enabled product development, such as LLM integrations, model orchestration, prompt/system design, retrieval-augmented generation, evaluation workflows, or AI-assisted automation. - Strong product judgment and a user-centered approach to building solutions that are robust, scalable, trustworthy, and easy to use. - Experience working in early-stage startups or similarly fast-moving, rapidly evolving environments; ideally, you have built products from 0 to 1. - Ability to navigate ambiguity, define technical direction, and deliver high-quality products in fast-paced environments. - Demonstrated success driving cross-team or cross-org alignment to get impactful work shipped. - Experience establishing engineering standards, component architectures, reusable patterns, and development best practices. - Leads through mentorship, actively developing peers and junior engineers while fostering a collaborative, high-performing engineering culture. - Entrepreneurial mindset: you take initiative, operate with ownership, and drive projects from concept through production impact. NICE TO HAVE - Experience building AI-powered products in healthcare, fintech, enterprise SaaS, or other high-trust domains. - Experience with evaluation, monitoring, and reliability practices for AI systems in production. - Familiarity with healthcare data, clinical workflows, privacy-sensitive systems, or regulated environments. - Experience building internal platforms or tooling that accelerate AI product development across engineering teams. Why You’ll Love It Here Please Note: the following benefits are for salaried employees - Hybrid work (SF office Mon/Tues/Thurs) + catered lunches (Bay Area Positions only) - Competitive salary, equity, and 401(k) - Wellness stipend & great benefits (medical, dental, vision) - Generous PTO & parental leave - Bi-annual offsites & a collaborative, mission-driven culture What to Expect in the Interview Process - Apply & meet our recruiting team - Virtual interviews to showcase your skills - Final onsite loop to meet the team and get to know us better - Chat with our CEO Curious to Learn More? - Read our Blog https://www.infinitus.ai/blog/ to hear from Infinauts about what we’re building - Discover how our company values (CODES https://www.infinitus.ai/careers/) guide us - Follow our CEO, Ankit Jain https://www.linkedin.com/in/jainankit/recent-activity/all/, for industry updates We’re building AI agents that tackle healthcare’s toughest problems and open new possibilities. Ready to join us? Let’s talk! Infinitus Systems is committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. Infinitus Systems believes that diversity and inclusion among our teammates is critical to our success as a global company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. Please Note: Applicants must be authorized to work in the US without employer sponsorship.
Data Scientist, Antifraud
WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHAT THIS ROLE MEANS AT HIGGSFIELD Generative video has a problem most subscription businesses don't: every unit we sell costs us real compute. A stolen password costs a streaming service nothing. An account farm on an unlimited generation plan costs us GPU-seconds, at scale, every hour it runs. We have found organised operators running hundreds of accounts on a single card, reselling unlimited generations, and harvesting per-account promotional grants at industrial scale. We have also found that most of our negative-margin accounts are not abuse at all — they are ordinary heavy users on an unlimited plan, which is a pricing problem wearing a fraud costume. Telling those two populations apart, at account level, before the money is gone, is this job. You own the question of who is taking value they did not pay for, and the system that stops them. You make sure: - We catch abuse before the compute is burned, not in a post-mortem that reconciles the loss - Every enforcement action has a measured precision, a measured cost of being wrong, and a way back for the customer we got wrong - The difference between fraud and unprofitable pricing is a number we can defend, not a vibe - When operators adapt — and they will, within days — we find out from a monitor, not from the monthly margin review WHAT YOU WILL DO Detection & scoring - Own the account-abuse scoring system end to end: signals, weights, thresholds, the scoring job, the monitoring, and the recalibration when it decays. - Build detection that fires early. A rule that catches 88% of the money on day 11 is worth far less than one that catches 60% at checkout, and you should be able to say why in dollars. - Work the two halves that actually matter together: linkage (who is connected to whom) and economics (what are they consuming). Either one alone produces a system nobody can switch on — linkage without economics flags families sharing a card, economics without linkage flags our best customers. - Treat cost as a gate, not a label. On an unlimited plan, being gross-margin negative is normal. Entity resolution & ring detection - Find rings, not just accounts: shared payment instruments, IP and ASN concentration, email-stem families, synchronised registration bursts, behavioural fingerprints, automation signatures. - Do it without a reliable device fingerprint — we do not have one today, and part of this job is telling us what it would be worth and what it would cost. - Know where graph methods break. Transitive closure through a shared card will happily merge thousands of unrelated people into one "ring"; we have done exactly that and thrown the result away. Enforcement, policy & the cost of being wrong - Design graduated, reversible actions — throttle, rate-limit, step-up verification, hold, pre-grant refusal, manual review queue, ban — and match the severity to the confidence. - Own the false-positive budget explicitly: how many paying customers are we willing to inconvenience to save a dollar of compute, and what is the appeal path for the ones we get wrong. - Build the pre-grant gates. The cheapest abuse to stop is the kind we decline to enable in the first place — a trial we do not grant costs nothing to claw back. - Partner with Payments on Stripe Radar, chargebacks and dispute economics; with Support on the queue your model creates; with Legal on what our Terms actually entitle us to do. Measurement & adversarial monitoring - Quantify what the system is worth in money — COGS avoided, net of the revenue you destroyed and the support cost you created. Keep that number current. - Run holdouts even on enforcement, wherever it is legal and safe to do so, because otherwise you will never know what your rules are worth. - Monitor for adaptation, not just drift. Model decay here is caused by an adversary, and it looks different: a signal stops firing, a ring changes shape, a cohort's behaviour shifts inside a week. - Watch your own inputs. A detection system that silently loses a feature degrades to a system that cannot reach its own threshold — and reports nothing wrong while doing it. Making it usable - Ship scores and reasons, never scores alone. An analyst, a support agent or an auditor must be able to read why an account was actioned. - Produce evidence that survives outside the company. Our abuse work has already been used in an external audit and in Terms-of-Use enforcement; write for that standard. - Work in SQL, Python and BigQuery on raw event, payment and generation data. We use AI heavily — resourcefulness beats syntax. WHO WE'RE LOOKING FOR - Experience building abuse, fraud or trust-and-safety detection that actually took action on real users — payments fraud, promo abuse, multi-accounting, bonus abuse, account takeover, marketplace or gaming abuse. Anti-money-laundering and credit-risk backgrounds transfer if the modelling was yours. - Genuine understanding of the adversarial setting: that your counterparty responds, that your training labels are generated by your own past decisions, and that offline AUC on a censored label set is close to meaningless. - Strong SQL and Python on raw event data without help: joins across payments, usage and identity, window functions, cohort replay. Gradient boosting, and the judgment to know when a two-condition rule beats a model. - Comfort with graph and linkage thinking — connected components, shared-attribute clustering, and an instinct for when a link is evidence and when it is coincidence. - Precision-first evaluation instincts: precision at the operating point, cost-weighted error, and why you would take 20% recall at 90% precision over the reverse in an enforcement system. - Unit-economics literacy: gross margin per account, what compute actually costs us, why a negative-margin customer may be entirely legitimate. - The judgment to escalate rather than act when the evidence is thin, and to say so in writing. - Clear written and spoken English, B2+. Backgrounds that often do well: - Fraud / risk data scientists from fintech, payments, marketplaces, gaming or crypto - Trust & safety and platform-integrity teams who owned detection and enforcement policy - Growth or product data scientists who ended up owning promo-abuse because nobody else would - Analysts from payment processors, PSPs or chargeback/dispute operations who moved into modelling WHAT THIS ROLE IS NOT This role is not a fit if you: - Want to build content-moderation or NSFW classification — that is a different function here - Would ship a ban list without knowing its precision - Optimize AUC on a label set your own enforcement created, and call it validated - Need a labelled fraud dataset to exist before you can start - Treat every negative-margin account as an abuser - Are uncomfortable that being right 90% of the time means being wrong about real, paying, legitimate people — and that you own what happens to them - Want predictable 9–5 workdays HIRING PROCESS We move fast: - Screening call (30 min) - Hiring-manager screen (30 min) - Business case (1 hour) - Practical home task (7 days) - Team interview (60 min) - Paid on-site trial (1 month) THE DEAL - Competitive salary in USD - Equity: participation in the company's stock option program - On-site role in Almaty, Kazakhstan - Relocation support (flight + temporary housing) - Flat structure, high autonomy, fast career growth
Test and Evaluation Engineer
Who we are Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We are growing our US operations, cultivating an ambitio u s and committed team of mission-driven professionals to apply their skills to solve challenging problems. The role In this role, you will be part of our hardware and platform integration team, focusing on the rigorous testing, validation, and evaluation of our Unmanned Aerial Vehicle (UAV) systems and AI-enabled flight capabilities. Your mission will span the complete development and deployment cycle: from laboratory-based software-in-the-loop (SIL) and hardware-in-the-loop (HIL) simulations to demanding field trials under real-world, degraded, and adversarial conditions. You will be an engineer who is not afraid to troubleshoot systems in the dirt, under rain, or in electromagnetically challenging environments, ensuring our platforms perform with extreme reliability and absolute safety when it matters most. The day-to-day - Design, build, and scale rigorous test and evaluation (T&E) pipelines for our autonomous UAV fleet, encompassing physical hardware, flight controllers, communication and sensor payloads, and AI edge-perception models. - Own planning and execution of Modeling and Simulation (M&S), Software-in-the-Loop (SIL), and Hardware-in-the-Loop (HIL) analysis to stress-test subsystem integrations and real-time software prior to physical flight. - Organize, coordinate, and execute flight test campaigns. Work closely with flight operators, field engineers, and software teams to validate autonomous behaviors, sensor synchronization, and edge-AI model performance under challenging real-world conditions. - Deep-dive into flight data logs, telemetry, and sensor streams to hunt down root causes of failures, sensor misalignment, or unexpected edge-case behaviors. Coordinate with M&S, SIL, and HIL engineers to perform post-test reconstruction and inform model updates and verification. - Collaborate directly with our software, ML research, and hardware design teams. You won't just report bugs; you'll partner directly to translate test findings into robust, hardened engineering solutions. - Author comprehensive test plans, safety cases, and qualification reports to satisfy safety benchmarks as well as military certification standards. Partner with System Engineers to produce artifacts necessary for Verification and Validation (V&V) of system performance. You should apply if you - Hold a BSc, MSc, or PhD in Aerospace Engineering, Robotics, Electrical Engineering, Physics, or a related technical field. - Have 7+ years of experience in testing, validation, and evaluation of complex autonomous systems, ideally UAVs, robotics, or aerospace platforms for US military customers. - Are highly proficient in Python, C++, or MATLAB for data analysis, log parsing, and automating validation setups. - Understand sensor integration, calibration, and synchronization (e.g., LiDAR, EO/IR cameras, IMUs, GNSS) and how they perform under vibration and thermal stress on an airframe. - Are perfectly comfortable navigating highly complex, multidisciplinary systems independently, troubleshooting them under pressure, and defining clear validation roadmaps. - Have experience on mature aircraft or munition development program, including operational testing. - Are familiar with the common military testing standards and designing tests for them. Examples include, MIL-STD 81H, MIL-STD 882E, MIL-STD 1316, etc... - Have hands-on experience with flight control systems (e.g., PX4, ArduPilot), ground control stations (QGroundControl), and communication datalinks. - Have a Part 107 or other pilot license. Note: We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarized in a few bullet points. Join Helsing and work with world-leading experts in their fields - Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns - The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world - Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defense industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward - In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts - We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practice responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about What we offer - A focus on outcomes, not time-tracking - A generous compensation and benefits package (in addition to base salary) that includes, but may not be limited to, insurance coverage (medical and travel), flexible paid time off, paid holidays, and remote and/or hybrid work available depending on position. All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time. The base salary offered to the successful candidate will be determined by a variety of factors including relevant experience, qualifications, education, skill level, interview performance, and the level and scope of the position. Helsing is an Equal Opportunity Employer. We will consider all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, genetics, or any other characteristic protected by applicable federal, state, or local law. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. Helsing's Candidate Privacy and Confidentiality Regime can be found here .
Software Engineer, Platform Engineering
Who we are Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations, cultivating an ambitious and committed team of mission-driven professionals to apply their skills to solve challenging problems. The role You will join the Platform Engineering team, which architects, builds, and maintains a developer-focused platform that powers all of Helsing US's product and project teams. You will design and operate cloud infrastructure, deploy and maintain shared services like GitLab, Artifactory, and CI/CD pipelines, and build internal tooling that accelerates software delivery across the organization. You will also enable product teams with their own isolated environments — provisioning cloud accounts, standing up EKS clusters, databases, and the automation to make it all self-service and efficient. Security is foundational to this role: the platform must meet CMMC Level 2 compliance requirements, and you will help ensure that the infrastructure and software supply chain are built to satisfy ATO and NIST security controls. The day-to-day - Designing and maintaining cloud infrastructure across a multi-account AWS environment using Terraform and Terraform Enterprise - Provisioning and managing EKS clusters, networking, IAM, and other AWS primitives for product and project teams - Standing up and operating shared services (GitLab, Artifactory, CI/CD pipelines) and other developer tooling - Building automation and self-service tooling that enables product teams to move quickly within secure guardrails - Designing and deploying agentic AI workflows to streamline developer activities, infrastructure operations, and platform compliance - Hosting and maintaining a mix of open-source, COTS, and internally developed services - Supporting MLOps workloads — enabling model training pipelines and managing secure data at scale - Building and maintaining observability and monitoring infrastructure for platform and product services - Collaborating with product teams to understand their infrastructure needs and translate them into scalable, repeatable platform capabilities - Working with engineering teams to ensure infrastructure meets CMMC and ATO requirements You should apply if you - Have 5+ years of experience in infrastructure, platform, or cloud engineering - Have a Bachelor's degree in Computer Science, Engineering, or a related field - Have strong experience with AWS, including GovCloud, multi-account architectures, Control Tower, IAM, VPC, EKS, and CloudFormation - Are proficient with Terraform and have managed infrastructure at scale across multiple accounts, ideally using Terraform Enterprise or Terraform Cloud - Have experience deploying and operating Kubernetes clusters in production - Are proficient in Python and Bash, with experience writing automation and infrastructure tooling - Are comfortable building and maintaining CI/CD pipelines and developer tooling - Understand security fundamentals including FIPS encryption requirements and can build infrastructure that satisfies compliance frameworks like CMMC and NIST - Can work across the stack, from cloud networking and IAM policies to Helm charts and container registries - U.S. citizenship required Nice to have - Experience with Go or other systems programming languages - Familiarity with ArgoCD and GitOps-based deployment patterns - Experience with SIEM platforms (e.g., Elastic) and centralized logging architectures - Experience supporting ML/AI workloads — GPU-backed instances, training pipelines, large dataset management - Background in defense, intelligence, or other regulated environments requiring ATO - Experience operating COTS products alongside custom-built internal services Join Helsing and work with world-leading experts in their fields - Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns - The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world - Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defense industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward - In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts - We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practice responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about What we offer - A focus on outcomes, not time-tracking - A generous compensation and benefits package (in addition to base salary) that includes, but may not be limited to, insurance coverage (medical and travel), flexible paid time off, paid holidays, and remote and/or hybrid work available depending on position. All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time. Helsing is an Equal Opportunity Employer. We will consider all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, genetics, or any other characteristic protected by applicable federal, state, or local law. Helsing's Candidate Privacy and Confidentiality Regime can be found here .
Backend Engineer, Agent Collaboration Platform
ABOUT HEBBIA The AI platform for investors and bankers that generates alpha and drives upside. Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for BlackRock https://www.blackrock.com/us/individual/about-us/about-blackrock?cid=ppc:blk_us:corpaffairs_us_br_reputationmediamanagement_na_exact_ol:google:brand_nonprod:ol&gclsrc=aw.ds&gad_source=1&gad_campaignid=21584717446&gbraid=0AAAAACc6WDFbRb5bgB6zxVFLE_7yIy25I&gclid=CjwKCAiA9aPKBhBhEiwAyz82J2uDlcIPVsy0fhSZMS_rp_OsGerYzYFPFfLo4TlN8K4eCHWzPfvysRoC7oQQAvD_BwE, KKR https://www.kkr.com/, Carlyle https://www.carlyle.com/, Centerview https://www.centerviewpartners.com/, and 40% of the world’s largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally. We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets. Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership. THE TEAM The Agent Collaboration platform team at Hebbia builds the interactive scratch-pad, analysis, and content creation tools for Agents. Our flagship product, Matrix, is a generative spreadsheet that leverages our ISD process https://www.hebbia.com/blog/goodbye-rag-how-hebbia-solved-information-retrieval-for-llms to coordinate complex agentic workflows across thousands of documents. We pair a simple, elegant interface—where users can kick off complex multistep document workflows—with a real-time, high-throughput LLM execution engine https://www.hebbia.com/blog/maximizer-hebbias-distributed-system-for-high-scale-llm-request-scheduling capable of processing the equivalent of 100 Harry Potter novels per second. Together, we turn massive, unstructured document repositories into seamless, actionable intelligence. THE ROLE A backend engineer at Hebbia blends expertise in systems, application layer software, and data modeling to build highly efficient software solutions. You will be responsible for leveraging the latest software and agentic solutions and integrating product experience with powerful distributed systems. You’ll help protect Hebbia’s technical edge via elegant software design, efficient data communication, and sophisticated integrations. We value engineers who move fast, hold themselves accountable to quality, and are detail-oriented. RESPONSIBILITIES 1. Own critical system components: Take complex requirements and turn them into robust, scaled solutions that solve real customer needs. 2. Unlock O(1) universal indexing: Build and iterate on our high-scale document build system that enables constant time latency for indexing any content in the world, regardless of data volume. 3. Drive performance optimization: Architect and implement performance-tuning solutions to ensure our systems operate efficiently at scale, minimizing latency and maximizing throughput across millions of documents. 4. Mentor and guide: Provide technical leadership, mentorship, and guidance to junior engineers, fostering a culture of learning and growth. WHO YOU ARE - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. A strong academic background with coursework in data structures, algorithms, and software development is preferred. - 5+ years software development experience at a venture-backed startup or top technology firm, with a focus on backend software engineering. - Proficiency in building backend and API systems using technologies such as Python, Java, or Go. - Extensive experience with cloud platforms (e.g., AWS) - Working experience with one or more of the following: Kafka, ElasticSearch, PostgreSQL, and/or Redis - Ability to analyze complex problems, propose innovative solutions, and effectively communicate technical concepts to both technical and non-technical stakeholders. - Proven experience in leading software development projects and collaborating with cross-functional teams. Strong interpersonal and communication skills to foster a collaborative and inclusive work environment. - Enthusiasm for continuous learning and professional growth. A passion for exploring new technologies, frameworks, and software development methodologies. - Embraces rapid prototyping with an emphasis on user feedback - Autonomous and excited about taking ownership over major initiatives - Bonuses: - Experience building agentic systems or LLM enabled products. - Frequent user of AI products, especially during the development lifecycle (i.e. Cursor, Claude Code, etc). COMPENSATION The salary range for this role is $160,000 to $350,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description. LIFE @ HEBBIA PTO: Unlimited Insurance: Medical + Dental + Vision + 401K Eats: Catered lunch daily + doordash dinner credit if you ever need to stay late Parental leave policy: 3 months non-birthing parent, 4 months for birthing parent Fertility benefits: $15k lifetime benefit New hire equity grant: competitive equity package with unmatched upside potential #LI-Onsite
Research Engineer
ABOUT HARMONIC At Harmonic, we are building a mathematical reasoning engine that operates with absolute precision. While most AI makes maximum-likelihood guesses, Harmonic's Aristotle uses Lean4 and reinforcement learning to verify its reasoning and results. Following our Gold Medal-level performance on the 2025 International Math Olympiad (IMO) and the successful resolution of long-standing open problems, we are proving that AI can master the most rigorous domains of human thought. Backed by some of the world’s most prominent investors, we are intentionally scaling an elite technical team. Visit our company blog https://harmonic.fun/news to learn more about what we are working on! ABOUT THE ROLE We are seeking a highly motivated and skilled Research Engineer to join our Reinforcement Learning & Formal Methods team. This position will be focused on advancing mathematical theorem proving using cutting-edge RL techniques. The successful candidate will play a key role in developing new algorithms and models that integrate RL with formal methods to solve complex problems in theorem proving and beyond. KEY RESPONSIBILITIES - Conduct high-quality research in the intersection of RL and formal methods, with a focus on mathematical theorem proving. - Develop and implement novel RL algorithms and models for theorem proving. - Collaborate with a multidisciplinary team to integrate RL techniques with formal methods. - Stay abreast of the latest developments in RL, formal methods, and related fields. MINIMUM QUALIFICATIONS - BS or MS in Computer Science, Mathematics a related technical field, or equivalent industry experience - Strong programming skills in Python, with experience in software development and testing. - Experience in deep learning frameworks such as PyTorch - Strong understanding of mathematical concepts, including algebra, geometry, and analysis. PREFERRED QUALIFICATIONS - PhD in Computer Science, Mathematics, or a related field. - Experience in applying AI to solve practical problems in formal methods. - Proven track record of high-quality research demonstrated by publications, patents, or software contributions. - Contributions to open-source projects or development of software tools in the field. - Strong background in RL, particularly in areas relevant to theorem proving (e.g., machine learning, natural language processing). - Proficiency in formal methods, including experience with theorem proving systems. WHAT WE OFFER - Unlimited PTO - 401(k) matching - 100% employer-paid health, vision, and dental benefits for employees and 50% coverage for dependents. Harmonic offers varied health coverage options to select what is best for you and your family. - Health Savings Account (HSA) available for qualifying health plans EQUAL OPPORTUNITY STATEMENT Harmonic is committed to diversity and inclusivity in the workplace. We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.
Senior Data Scientist, Product Analytics
ABOUT THE ROLE We’re looking for a Senior Data Scientist, Product Analytics to lead analytics for Handshake’s Recruiting marketplace. You’ll drive measurement and strategy across marketplace health, liquidity, pricing, and product-led growth, partnering closely with Product, Engineering, and Leadership to shape the future of our marketplace. This is a highly impactful, hands-on role where you’ll own analytics strategy, influence product direction, and work alongside our Relevance (ML) team to ensure our models deliver measurable business impact. WHAT YOU’LL DO - Partner with Product, Engineering, and R&D leadership to define and measure marketplace health, liquidity, pricing, and growth. - Own analytics strategy, domain metrics, goal setting, and reporting for your product area. - Lead experimentation, including test design, instrumentation, analysis, and recommendations. - Partner with our Relevance team to evaluate and benchmark machine learning models. - Conduct deep analyses across user behavior, funnels, cohorts, and marketplace performance to uncover actionable insights. - Collaborate with Analytics Engineering to define trusted metrics and scalable data models. - Build dashboards and reporting that enable fast, data-driven decision making. - Champion AI-powered workflows and help shape the future of Product Analytics at Handshake. DESIRED CAPABILITIES - 5+ years of experience as a Data Scientist or Product Analyst driving product strategy through data. - Expert-level SQL skills with experience analyzing large, complex datasets. - Strong experience with experimentation, A/B testing, and statistical analysis. - Experience partnering closely with Product Managers, Engineers, and cross-functional stakeholders. - Python experience for analytics (e.g., Jupyter notebooks, pandas). - Strong business intuition with the ability to translate data into strategic recommendations. - Excellent communication skills and the ability to influence technical and executive audiences. - High ownership mindset with the ability to independently drive ambiguous projects to completion. EXTRA CREDIT - Experience working on marketplace, pricing, or growth analytics. - Experience supporting machine learning model evaluation or benchmarking. - Experience with BI and visualization tools such as Hex, Mode, or similar platforms. - Enthusiasm for AI-first ways of working and leveraging AI tools to accelerate analysis and decision making. PERKS - Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, wellness stipend 📚 Growth: Learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
Member of Technical Staff, Evals
ABOUT HANDSHAKE Handshake's mission is to organize expert human knowledge to advance the AI economy. Handshake AI works directly with frontier labs on their most consequential data, evaluation, and post-training challenges, building the systems that turn expert human knowledge into the data and evaluations that make frontier models better. You will work alongside engineers, researchers, operators, and builders from organizations including Scale AI, Meta, Google, Amazon, xAI, Notion, and Palantir—and help build the systems that make expert human knowledge useful for advancing AI. THE ROLE We are hiring a Member of Technical Staff, Evals to help define how frontier AI systems are measured, understood, and improved. This is a broad, high-ownership role for researchers who build. You will partner with AI researchers, domain experts, and customers to develop new benchmarks, reward and verifier systems, agent-evaluation methodologies, and data-quality techniques. You will work on questions at the center of frontier AI progress: what should be measured, how to design evaluations that reflect real capability, how to create high-signal feedback, and how to build the environments and data systems that make those answers actionable. Early members of the team will have unusual influence over our technical direction, operating culture, and the open-source software, benchmarks, and research products we build. We care more about demonstrated research capability, technical judgment, and a builder's mindset than a specific title, degree, or career path. Location: San Francisco preferred; we are open to exceptional candidates in other locations. WHAT YOU'LL DO - Design and build evaluation frameworks, benchmarks, and methodologies for frontier LLMs, AI agents, multimodal models, and reinforcement-learning environments. - Develop reward models, programmatic verifiers, graders, and other feedback systems that make model behavior measurable and improvable. - Research what makes evaluations representative, difficult, reliable, and resistant to shortcutting or reward hacking. - Build systems for high-quality human data, including expert task design, annotation methodologies, data-quality signals, and data-attribution techniques. - Run fast, rigorous iteration loops: prototype, evaluate, interpret results, diagnose failure modes, and turn learnings into the next benchmark or system. - Publicly contribute to the field through benchmarks, open-source tools, research, and technical writing. WHAT WE'RE LOOKING FOR - PhD in ML/AI, computer science, data science, or related fields (or equivalent research experience in industry). - Publications at top AI/ML venues like NeurIPS, ICML, ICLR, COLM. - Builders who enjoy tinkering with agents and shipping high-quality software, benchmarks, or datasets (e.g. a strong GitHub profile / OSS contributions, or product portfolio). - Strong Python skills, experience building scalable software, working with agents. - Strong knowledge of frontier AI: benchmarks, eval techniques, agent harnesses, post-training recipes, data shapes. - Comfort operating in an ambiguous, fast-moving environment with substantial ownership. WHY JOIN - Work at the very frontier of AI with most major AI labs, researching some of the most important problems in Data and Evaluations. - Publish results and work in public through open-source benchmarks and software, papers, and blogs. - Join a rapidly growing company whose data business grew from zero to nearly $1B run rate in a year. - Help build an early technical organization where your work shapes the roadmap, standards, and culture. - Attend (and publish at) conferences like NeurIPS, ICML, ICLR, COLM. PERKS Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend 📚 Growth: $2,000 learning stipend, ongoing development 💻 Office: Commuting support, free lunch, and gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses
Data Scientist, Handshake AI
ABOUT HANDSHAKE AI Handshake AI is the fastest-growing, most critical, and most revenue-generating part of Handshake's business. We power expert-labeled data collection at scale, matching domain experts with leading AI companies to train frontier models—and we're already a top-three player in one of the fastest-growing sectors in AI: human data. We have the opportunity to do for the AI data economy what LinkedIn did for professional networking: become the default platform where the work happens. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world's top educational institutions - Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others - Build a massive, fast-growing business with billions in revenue ABOUT THE ROLE We’re looking for a highly motivated Data Scientist with strong SQL expertise to support analytics, measurement, and operational insights across our human data training workflows. You’ll work with messy, fast-moving data related to expert performance, task quality, throughput, and overall operational efficiency. This is a hands-on role with real ownership, close partnership with product and operations, and a steep growth curve for someone who executes well. WHAT YOU’LL DO - Write advanced SQL to analyze large, complex datasets related to expert performance, task quality, and operational workflows. - Define, build, and maintain core metrics that measure data quality, throughput, productivity, and operational efficiency. - Partner with Product, Operations, and cross-functional stakeholders to answer high-impact business and product questions. - Conduct analyses that inform workflow design, task improvements, and operational decision-making. - Build dashboards, reporting, and self-serve analytics that enable fast, informed decisions. - Identify data gaps, inconsistencies, and quality issues, then partner with relevant teams to resolve them. - Translate ambiguous business questions into clear analyses and actionable recommendations. - Communicate findings and recommendations clearly to both technical and non-technical stakeholders. DESIRED CAPABILITIES - 3–5 years of experience in Data Science, Product Analytics, Business Intelligence, or a related analytical role. - Expert-level SQL skills and experience working with large, complex datasets. - Strong analytical judgment and comfort working with imperfect, real-world data. - Experience defining metrics and using data to influence product or business decisions. - High ownership mindset and ability to independently drive complex work forward. - Strong communication skills and comfort partnering cross-functionally in a fast-paced environment. EXTRA CREDIT - Python experience for data analysis, such as pandas and notebooks. - Experience supporting operational, marketplace, quality, or workforce-related analytics. - Experience with experimentation, A/B testing, or metrics-driven product development. - Exposure to AI data workflows, data labeling, or evaluation processes. - Experience with analytics engineering, including building and maintaining DBT models. PERKS - Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, wellness stipend 📚 Growth: Learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers http://joinhandshake.com/careers.
AI Safety Policy Evaluator, Violence & Threats | S...
This is a non-engineering content-policy evaluation role. Applicants must demonstrate relevant depth in violent fiction or media, military or emergency response, crisis or threat assessment, trust and safety, content moderation, or closely related policy work. Software engineering or LLM product experience alone is not sufficient. ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. Handshake AI works directly with frontier AI lab researchers to create evaluations, publish benchmarks, and improve AI models through human expertise. ROLE DETAILS Location: Onsite in Seattle, WA, Monday-Friday. Compensation: $55-$120/hr. Placement within the range depends on experience. Employer: TCWGlobal. This is a W-2 assignment supporting Handshake AI. Employment: Full time, 40 hours per week, non-exempt and eligible for overtime pay. Schedule: Monday-Friday, 8 a.m.-5 p.m. PT. Assignment: Ongoing. ABOUT THE ROLE As an AI Safety Policy Evaluator focused on Violence & Threats, you will help AI models learn where the line falls between depicting violence and enabling it. Violence is one of the hardest domains in AI safety because most violent content is legitimate. Novels, games, screenplays, history, journalism, self-defense, and ordinary human frustration all involve violence, and a model that refuses them is broken. A model that helps someone plan real harm is worse. Your job is to tell the difference, case by case, and to explain your reasoning clearly enough that it can train a model. You will read user requests, model responses, and conversation history, then decide which policy category applies and whether the model's response was appropriate. The interesting cases are the close ones: a torture scene that is either a chapter of a thriller or an interrogation manual with character names; a message that reads as venting about a boss or as a plan; a "realistic" combat question from a novelist that is also a real-world capability question. One word, one contextual detail, or one shift in intent changes the answer. We are looking for people who already have strong instincts about violence in at least one of these areas: how it works in fiction, how it works in the real world, or how it shows up in people who are struggling. You do not need all three. You need one deep and the judgment to learn the rest. This is not rote annotation. Policies cannot anticipate every edge case, and good evaluators do not apply them mechanically. You will balance policy text and intent with customer expectations, conversation context, precedent, and team calibration. WHAT YOU WILL DO - Evaluate user requests and AI model responses involving violence, weapons, threats, and dark fiction within the full conversation context; maintain accuracy and consistency across repeated evaluations - Distinguish fictional, educational, historical, and defensive violence from requests that seek real-world uplift or express real intent to harm - Assess whether a model's response gives meaningful real-world capability, regardless of how the request was framed - Distinguish expressions of anger, frustration, or dark humor from credible threats or crisis indicators - Select the most defensible classification when a case is genuinely ambiguous, and write concise rationales that cite policy language and conversation details while applying customer policy consistently - Write and refine adversarial or borderline prompts that probe where a model draws the line - Identify policy gaps, contradictions, and emerging edge cases, and raise them with project leads and policy teams - Participate actively in calibration discussions; challenge interpretations respectfully and update your judgment when stronger reasoning emerges YOU MAY BE A FIT IF - You have spent serious time in violent fiction as a writer, game master, game designer, screenwriter, or editor, and you know what good dark fiction looks like and what a story-shaped extraction attempt looks like - You have real-world exposure to violence and its consequences through military, law enforcement, security, EMS, emergency medicine, or similar work, and you can tell movie logic from what actually works - You have worked with people in distress through crisis lines, counseling, threat assessment, domestic violence advocacy, school safety, or trust and safety, and you know the difference between "I could kill him" and a plan - You use AI tools heavily and have opinions about where they refuse too much, help too much, or miss the point - You notice when one word, contextual detail, or change in intent materially affects the answer - You can hold a strong opinion without becoming attached to being right - You explain judgment calls clearly and precisely in writing so another person can audit your reasoning - You can separate your personal views from the standard a customer has asked you to apply and remain careful and consistent during repetitive work with difficult material Strong candidates may come from fiction writing, game design or game mastering, film and TV, military or law enforcement, emergency medicine, crisis counseling, threat assessment, trust and safety, content moderation, journalism, or law. We care more about how you reason than where you learned to reason. A degree, a clearance, and a technical background are not required. NICE TO HAVE - Published or produced work involving violence: novels, short fiction, screenplays, comics, tabletop or video game content, mods, or fan fiction with an audience - Military, law enforcement, corrections, private security, or armed professional experience - Training or professional experience in crisis intervention, threat assessment, forensic or clinical psychology, or violence prevention - Experience with firearms, martial arts, or other weapons disciplines as an instructor, competitor, or professional - Prior work in AI evaluation, red teaming, data annotation, RLHF, trust and safety, or content moderation - Experience evaluating outputs from ChatGPT, Claude, Gemini, or other language models in a professional capacity - Familiarity with calibration sessions, inter-rater agreement, or adjudication workflows SENSITIVE-CONTENT NOTICE This role involves regular and deliberate engagement with graphic material. This is the core of the job, not an occasional part of it. Evaluations will routinely include depictions of violence, weapons, torture, abuse, threats, self-harm, and death, including violence against vulnerable people, along with the emotional distress that often surrounds it. The work is conducted within structured evaluation frameworks and professional guidelines, with exposure limits, content rotation, and access to mental health support. Candidates must be able to engage with this material carefully, responsibly, and sustainably while maintaining sound judgment and consistent work quality. BENEFITS Benefits are provided through TCWGlobal. Eligible employees can enroll in medical coverage, including prescription and mental health benefits, dental and vision insurance, healthcare and dependent care flexible spending accounts, and pretax commuter benefits. A 401(k) retirement plan with an employer match is available to eligible participants. Additional offerings include voluntary accident, critical illness, and term life insurance, wellness and pet-related reimbursements, charitable matching, and employee discounts. Eligibility requirements, waiting periods, employee contributions, and plan terms apply. Full-time employees scheduled for at least 30 hours per week are eligible for health coverage beginning the first of the month following at least 30 days of employment. Retirement plan eligibility follows a separate schedule. Paid time off: PTO accrues from the first day of the assignment at one hour per 40 hours worked, with no waiting period to use accrued PTO. PTO may be used for vacation, personal days, or illness, subject to policy approval requirements. Accrual is capped at 80 hours per year and balances at 100 hours, unless otherwise required by law. Additional paid sick leave is provided in accordance with applicable Washington and Seattle requirements. Paid holidays: The holiday policy lists 13 paid holidays. Eligible employees receive eight hours of holiday pay at their base hourly rate for observed holidays that fall on a scheduled workday, subject to the holiday policy. See the TCWGlobal 2026 Benefits Guide https://www.tcwglobal.com/benefitsguide-basic-2026 for coverage options, costs, and enrollment details. INTERVIEW PROCESS The process includes application review, a recruiter screen, a skills assessment, a hiring manager screen, onsite interviews, and a final round before the offer stage. Your recruiter will share the next steps as you move through the process. EQUAL OPPORTUNITY AND ACCOMMODATIONS TCWGlobal is an equal opportunity employer. Hiring decisions are based on qualifications and abilities, without discrimination based on characteristics protected by applicable law. Reasonable accommodations are available during the application and interview process. If you need an accommodation, please let your recruiter know.
AI Model Policy Trainer, Generalist (Seattle)
ABOUT HANDSHAKE Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions. Handshake AI works directly with frontier AI lab researchers to create evaluations, publish benchmarks, and improve AI models through human expertise. ABOUT THE ROLE As an AI Model Policy Trainer, Generalist, you will turn complex customer policies into consistent, well-reasoned evaluations of AI model behavior. You will read user requests, model responses, and relevant conversation history, then determine which policy category best applies. The most interesting cases will not have obvious answers. Two examples may look almost identical until a single word, contextual detail, or difference in intent changes the correct classification. We are looking for people who enjoy splitting hairs in a healthy way. You form clear opinions, explain precisely why two cases should be treated differently, challenge interpretations respectfully, and change your mind when better evidence emerges. Productive disagreement helps the team find the most accurate and consistent interpretation. Policies cannot anticipate every possible edge case. You will balance the policy’s text and intent with customer expectations, conversation context, precedent, and team calibration. The subject matter will vary across projects, from distinguishing benign assistance from meaningful facilitation of harm to evaluating emotional reliance or nuanced sexual-safety boundaries. Success requires learning each customer’s framework on its own terms. WHAT YOU WILL DO - Learn customer policies, definitions, taxonomies, and evaluation rubrics, and adapt as projects and guidance change. - Evaluate user requests and AI model responses within the full relevant conversation context. - Distinguish between closely related labels, severity levels, and policy boundaries to select defensible classifications. - Write concise, evidence-based rationales citing relevant policy language and conversation details. - Identify policy gaps, contradictions, and emerging edge cases, and raise questions when guidance does not resolve a case. - Participate in calibration discussions with evaluators, project leads, policy teams, and researchers; challenge interpretations respectfully and update your judgment when evidence warrants it. - Apply customer policy consistently, maintain accuracy across repeated evaluations, and incorporate feedback into future work. - Help improve evaluation frameworks, examples, decision rules, and quality standards. YOU MAY BE A FIT IF - You enjoy precise distinctions and notice when one word, contextual detail, or change in intent affects the answer. - You can hold a strong opinion without becoming attached to being right and discuss disagreement respectfully. - You explain judgment calls clearly enough that another person can audit your reasoning. - You ask productive questions when a policy is ambiguous instead of guessing or forcing certainty. - You separate personal views from the customer’s standard while understanding both the letter and purpose of a policy. - You remain careful and consistent during repetitive work and apply feedback quickly. - You learn unfamiliar subjects quickly, work independently, and recognize when you need more context. - You treat sensitive information and difficult subject matter with maturity and sound judgment. Strong candidates may come from quality assurance, research, editing, law, teaching, operations, trust and safety, content moderation, social science, policy, investigations, compliance, customer support, or other fields that require careful interpretation and defensible decision-making. We care more about how you reason than where you learned to reason. NICE TO HAVE - Professional experience evaluating language models or working in AI evaluation, data annotation, RLHF, trust and safety, or content moderation. - Experience applying detailed rubrics, taxonomies, regulatory language, or quality frameworks. - Familiarity with calibration, quality audits, adjudication, or writing policy guidance and evaluation examples. - Comfort evaluating long conversations, incomplete context, and conflicting evidence, with an interest in AI safety. SENSITIVE-CONTENT NOTICE This role involves regular and deliberate engagement with sensitive material. Depending on the project, evaluations may include sexual content, emotional distress, self-harm, suicide, violence, weapons, abuse, exploitation, discrimination, and other potentially disturbing subjects. The work is conducted within structured evaluation frameworks and professional guidelines. Candidates must be able to engage with this material carefully, responsibly, and sustainably while maintaining sound judgment and consistent work quality. ROLE DETAILS - Location: Onsite in Seattle, WA, Monday–Friday. - Compensation: $30-$85/hr. Placement within the range depends on experience. - Employer: TCWGlobal. This is a W-2 assignment supporting Handshake AI. - Employment: Full time, 40 hours per week, non-exempt and eligible for overtime pay. - Schedule: Monday–Friday, 8 a.m.–5 p.m. PT. BENEFITS Benefits are provided through TCWGlobal. Eligible employees can enroll in medical coverage, including prescription and mental health benefits, dental and vision insurance, healthcare and dependent care flexible spending accounts, and pretax commuter benefits. A 401(k) retirement plan with an employer match is available to eligible participants. Additional offerings include voluntary accident, critical illness, and term life insurance, wellness and pet-related reimbursements, charitable matching, and employee discounts. Eligibility requirements, waiting periods, employee contributions, and plan terms apply. Full-time employees scheduled for at least 30 hours per week are eligible for health coverage beginning the first of the month following at least 30 days of employment. Retirement plan eligibility follows a separate schedule. Paid time off: PTO accrues from the first day of the assignment at one hour per 40 hours worked, with no waiting period to use accrued PTO. PTO may be used for vacation, personal days, or illness, subject to the policy’s approval requirements. Accrual is capped at 80 hours per year and balances at 100 hours, unless otherwise required by law. Additional paid sick leave is provided in accordance with applicable Washington and Seattle requirements. Paid holidays: The holiday policy lists 13 paid holidays. Eligible employees receive eight hours of holiday pay at their base hourly rate for observed holidays that fall on a scheduled workday, subject to the holiday policy. See the TCWGlobal 2026 Benefits Guide https://www.tcwglobal.com/benefitsguide-basic-2026 for coverage options, costs, and enrollment details. INTERVIEW PROCESS The process includes application review, a recruiter screen, a skills assessment, a hiring manager screen, onsite interviews, and a final round before the offer stage. Your recruiter will share the next steps as you move through the process. EQUAL OPPORTUNITY AND ACCOMMODATIONS TCWGlobal is an equal opportunity employer. Hiring decisions are based on qualifications and abilities, without discrimination based on characteristics protected by applicable law. Reasonable accommodations are available during the application and interview process. If you need an accommodation, please let your recruiter know.
Staff Data Engineer – Agentic Applications
About us Graphcore is one of the world's leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world's most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore's teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. Job Summary Reporting to the Head of Data & Transformation, the Staff Data Engineer – Agentic Applications is a senior individual contributor responsible for designing, building and operating Python-based web applications, agentic workflows and supporting data services for Graphcore’s business teams. The role combines strong data engineering foundations with hands-on application development, using AI agents, trusted data and business system integrations to improve decision-making and automate operational workflows. Depending on the use case, you will either deliver applications end to end, using AI-assisted coding tools to build and maintain the front end, or own the backend and enable business colleagues to create and look after their own front ends. In both approaches, you will help establish clear ownership, secure interfaces and appropriate engineering controls so applications remain reliable, maintainable and supportable. Working closely with engineers, analysts and business stakeholders, you will take solutions from initial requirements through to production, contribute to the evolution of the underlying data platform and provide technical leadership through design reviews, code reviews and mentoring. The Team The Data & Analytics team enables better decision-making across Graphcore by building trusted data foundations, scalable platforms and high-quality data products. The team works across a broad range of business and technical domains, partnering with colleagues throughout the company to improve access to reliable information, strengthen operational insight and support efficient, data-informed ways of working. Within this team, the Staff Data Engineer – Agentic Applications turns these foundations into practical business applications and automated workflows. The role also enables colleagues outside engineering to participate in application development, supported by reusable services, clear guidance and appropriate governance. Responsibilities and Duties - Build business-facing applications. Design, develop and operate production-ready Python web applications that help business teams access trusted data, complete tasks and improve operational workflows. - Develop agentic capabilities. Build applications and workflows that connect AI agents to approved tools, APIs, datasets and business systems, with clear boundaries on what agents can access and do. - Translate business needs into working solutions. Partner with analysts, engineers and business stakeholders to understand user needs, identify appropriate opportunities for automation and take applications from prototype through to supported production services. - Deliver end-to-end applications where appropriate. Use AI-assisted coding tools to build and maintain front ends alongside Python backend services, taking responsibility for the quality, testing, security and maintainability of generated code. - Enable business-owned front ends. Where business teams develop and maintain their own interfaces, own the backend and provide documented APIs, reusable templates, examples and practical coaching so colleagues can work effectively with AI-assisted coding tools. - Establish clear ownership and support arrangements. Agree responsibilities for application changes, testing, releases and ongoing support, including appropriate review and deployment controls for business-maintained front ends. - Build secure, reusable backend services. Design APIs and application services that enforce authentication, authorisation, input validation and business rules, keeping secrets and sensitive operations within controlled backend systems. - Engineer reliable agentic workflows. Implement appropriate evaluation, monitoring, audit trails and safeguards, including constrained tool permissions, human approval for consequential actions and safe handling of failures or unreliable model outputs. - Maintain strong data foundations. Design, build and enhance Python-based batch and streaming pipelines, trusted datasets and reusable data models that support applications, analytics, reporting and operational workloads. - Own key platform components. Take ownership of relevant backend and data-platform services, using AWS services including S3, Lambda, Aurora PostgreSQL, Athena, Glue and Redshift to deliver secure, resilient and cost-effective solutions. - Enable safe, repeatable delivery. Build and maintain orchestration, CI/CD workflows, automated testing, deployment processes, monitoring and operational support for applications and data workflows. - Improve resilience and performance. Apply robust error handling, idempotent processing, retry and recovery mechanisms, and backfill or replay capabilities to improve reliability, scalability and operational performance. - Apply engineering and governance standards. Contribute to standards for data quality, documentation, observability, security and access management, including least-privilege access, database permissions and secure secrets handling. - Provide technical leadership. Review designs and code, mentor engineers and guide business application builders, helping raise engineering quality across both manually written and AI-generated software. - Improve shared capabilities. Identify opportunities to simplify delivery, reuse application patterns and enhance platform capabilities, contributing to technical roadmaps and engineering practices across the Data & Analytics team. Candidate Profile Essential - Strong experience designing, building and operating production-grade data pipelines and platforms using Python. - Experience building and supporting Python web applications, backend services and APIs that integrate data and business systems. - Practical experience developing applications or workflows that use large language models or AI agents, including connecting them to tools, APIs and governed data sources. - Experience using AI-assisted coding tools effectively, with the ability to understand, review, test, debug and maintain generated code rather than relying on generated output without validation. - Ability to either build usable web front ends with AI-assisted tools or enable business colleagues to develop and maintain front ends against well-defined backend services. Sufficient understanding of web development to review integrations and troubleshoot application behaviour is required; deep specialist front-end expertise is not essential. - Strong hands-on experience with modern orchestration, automated testing, CI/CD, deployment and monitoring practices in production environments. - Experience building cloud-based solutions using AWS services, including data storage, processing and query technologies. - Strong understanding of data modelling, schema design, data quality and performance optimisation across relational and analytical systems. - Experience working with both batch and streaming data pipelines, including operational support, troubleshooting and designing systems that recover gracefully from failures. - Strong understanding of security, access control and governance for cloud-based data platforms and applications, including authentication, authorisation, IAM, database permissions and secure secrets management. - Practical understanding of the reliability and security considerations of agentic applications, including permission boundaries, evaluation, auditability and appropriate human oversight. - Experience providing technical leadership as a senior individual contributor through design reviews, code reviews, engineering standards and mentoring. - Ability to collaborate effectively with technical and non-technical stakeholders, translate business requirements into practical, scalable solutions and explain technical concepts clearly. - Ability to coach business colleagues in AI-assisted application development and establish clear boundaries between business-owned interfaces and engineering-owned services. Desirable - Experience with Python web application frameworks such as Streamlit, Flask or FastAPI. - Working knowledge of JavaScript or TypeScript and a modern front-end framework. - Experience with agent orchestration, retrieval over business data, or automated evaluation of AI-enabled applications. - Experience with Prefect or a similar workflow orchestration platform. - Experience with streaming or data collection technologies. - Experience with PostgreSQL, Redshift, ClickHouse or similar database and data warehouse technologies. - Experience with Infrastructure as Code and reusable application deployment patterns. - Familiarity with dbt and analytics engineering practices. - Experience improving observability, operational monitoring, application performance and cloud cost optimisation. - Experience contributing to technical roadmaps and platform improvements within a collaborative engineering team. - Experience working within a fast-moving technology or engineering environment. Benefits In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications
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