AI Engineering Jobs in San Francisco

NVIDIA is seeking an AI & Deep Learning Compiler Engineer to join its Deep Learning & AI Compiler (DLC) team. This role involves developing and optimizing the compiler that powers NVIDIA's inference engine across various platforms, from data centers to personal devices. The compiler is crucial for delivering leading inference performance, fast build times, reduced memory footprints, and ease of use for the global deep learning community. You will contribute to the next era of computing by enabling breakthroughs in areas like large language models and generative AI.

$152k - $242k

NVIDIA's DGX Cloud team is seeking a Senior Full-Stack Software Engineer to join the AI Hub team. This role will accelerate AI research by ensuring NVIDIA's AI infrastructure is used efficiently, transparently, and at scale. The primary goal is to build a unified, self-service portal for AI researchers to manage, monitor, and optimize their use of Managed AI research Superclusters. You will lead the architecture and delivery of high-scale web products, own multi-team initiatives, and drive reliability and performance improvements.

$224k - $357k

NVIDIA is seeking a Senior Backend Compiler Engineer to join our GPU Software organization. This role focuses on constructing and emitting high-performance GPU machine instructions for Graphics and Compute applications. You will be instrumental in designing and implementing a new LLVM-based JIT compiler targeting NVIDIA GPUs, developing new compiler passes and optimizations, and collaborating with global teams to drive improvements and problem resolution. This is an opportunity to apply and adapt cutting-edge compiler technologies to produce premier, robust compiler tools and influence new GPU architectures.

$152k - $242k

NVIDIA IT's Enterprise AI & Automation team is seeking a Principal or Distinguished Engineer to architect and build enterprise-grade agentic AI systems. This role involves hands-on coding in Python and/or Go to develop production AI agents that securely integrate with enterprise systems, enhancing employee efficiency and business outcomes across various departments. The ideal candidate will be a technical leader who can translate new agent development patterns into scalable platform capabilities, define NVIDIA's enterprise agent architecture through practical implementations, and drive the full agent development lifecycle from creation to continuous enhancement. This position is for a deeply involved technical leader who writes code daily and thrives in ambiguous environments, rapidly moving from concepts to operational systems. You will invent systems incorporating persistent memory, controlled runtimes, strict assessment, and GPU-powered performance to ensure agents are intelligent, trackable, protected, and production-ready.

$272k - $431k

NVIDIA is seeking an AI Storage Platform Architect to bridge the gap between advanced hardware and AI deployments. This role involves translating the capabilities of NVIDIA's latest hardware, including Rubin GPUs, Vera CPUs, BlueField DPUs, NVLink, and Spectrum-X networking, into production-ready blueprints. You will collaborate with storage ecosystem partners to co-develop reference architectures for the NVIDIA AI Data Platform, optimizing every layer of the stack for AI workloads. This is an opportunity to work in a diverse and supportive environment, making a significant impact on the future of computing.

$224k - $357k

We are seeking a visionary Developer Relations Manager to engage with the next generation of AI-native software companies. In this role, you will partner directly with AI-native founders, product leaders, and engineering teams to help them design, optimize, and scale their AI platforms on NVIDIA technologies. You will guide companies building agentic systems, AI copilots, developer tools, reasoning models, and multimodal AI applications, helping them accelerate training, optimize inference, and deliver world-class AI experiences. The ideal candidate combines deep technical expertise in AI in systems, developer platforms, and large-scale inference infrastructure with a passion for working alongside ambitious startup founders and engineers.

$152k - $288k

NVIDIA is seeking a Senior Engineering Manager to lead and define the company's JAX strategy. This role involves coordinating multiple teams and workstreams to ensure JAX delivers peak performance across NVIDIA's evolving datacenter infrastructure, which includes GPUs, CPUs, and LPUs. The position is critical for ensuring JAX is ready on next-generation architectures and supports emerging AI needs across training, post-training, inference, and robotics, bridging new hardware capabilities with AI trends.

$272k - $431k

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC-gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU-accelerated deep learning ignited modern AI—the next era of computing—with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” Our Enterprise AI team builds intelligent AI agents that transform how NVIDIA operates — from smart personal assistants and engineering-productivity tools to data-driven analytics and supply-chain optimization. These agents are live, in production, and used across the company. Now we need a principal-level, hands-on engineering leader to make them bulletproof and to architect the next generation of agent infrastructure. This is not a research role. This is a role for someone who obsesses over reliability, polish, and user trust — and who has the full-stack depth to harden production systems and the architectural vision to ensure they scale. What you'll be doing: - Improve reliability, performance, observability, release confidence, and end-user experience across desktop, web, and service-based AI products. - Design and build resilient frontends, backend APIs, distributed services, data flows, and deployment systems that scale to enterprise use. - Establish strong patterns for testing, debugging, CI/CD, safe rollout, auto-update mechanisms, monitoring, incident response, and operational excellence so our Agentic AI applications behave like mature software, not prototypes. - Build reusable capabilities that support multiple agent domains, including orchestration services, deep-agent workflows, memory and context services, evaluation frameworks, telemetry, and policy-aware tool integration. - Help validate and operationalize technologies such as Nemotron, NVIDIA AI Blueprints, and related platform capabilities in enterprise production settings. - Codify architecture, shared components, documentation, and operational playbooks; mentor engineers; and create foundations that are durable, reusable, and broadly owned. - Define the core architecture for how AI agents discover one another, collaborate securely, build trust, and operate under enterprise governance. - Partner closely with domain AI engineers, product managers, designers, infrastructure teams, IT, and research to deliver measurable outcomes across employee productivity, engineering efficiency, AIOps, and enterprise operations. What we need to see: - BS, MS, or equivalent experience in Computer Science or a related field. - 15+ years building and operating production software systems, including significant experience leading architecture and delivery across the full stack. - Familiarity with enterprise application deployment, security, authentication, device management, and application lifecycle management. - Solid experience building modern applications across frontend, backend, and platform layers. This may include technologies such as TypeScript/JavaScript, React, Electron or similar desktop frameworks, Python, Go, Java, APIs, data systems, and distributed infrastructure. - Proven track record taking complex products from prototype to reliable, secure, well-operated production systems. Deep expertise in testing strategy, release engineering, observability, performance tuning, and incident response. - Experience building shared services, internal platforms, SDKs, or core infrastructure used by multiple teams or products. - Working knowledge of modern AI application patterns such as LLM-powered applications, RAG, tool use, CLI-based workflows, reusable skills, MCP-based integrations, evaluation loops, memory systems, and agentic workflows. You do not need to be a research scientist, but you should know how to build reliable, production-grade systems around AI. - Strong judgment, communication, and cross-functional leadership skills, with the ability to influence across teams while remaining highly hands-on. Ways to stand out from the crowd: - Experience hardening desktop or client applications at scale, including installers, auto-update systems, crash recovery, and enterprise distribution. - A track record of improving engineering velocity and consistency through common frameworks, platform services, design patterns, and developer tooling. - Experience building reusable infrastructure for AI products, such as orchestration layers, memory/context services, evaluation platforms, human-in-the-loop workflows, or policy and safety controls. - Familiarity with identity, discovery, trust, reputation, or graph-based systems relevant to large-scale agent collaboration. - Experience with GPU-accelerated systems or NVIDIA AI technologies such as NeMo, NIM, Nemotron, TensorRT-LLM, or AI Blueprints. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until November 3, 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.

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NVIDIA is seeking a Senior Robotics Research Engineer to join its Seattle Robotics Lab, focusing on AI and robotics for drug discovery. This role involves developing fundamental robotics technology and building real-world systems to automate and bring autonomy to molecular discovery, manufacturing, testing, and validation. You will work on creating digital twins of robots and lab environments, simulating robot physics, developing perception pipelines, and translating experimental protocols into executable physical procedures. The position requires training robots for complex manipulation tasks and integrating these systems into biological experiment workflows, collaborating with research scientists and engineers across NVIDIA and Eli Lilly.

$184k - $288k

Join the CPU performance architecture team to drive the development of CPU technology for diverse applications including AI/deep learning, high-performance computing, cloud services, gaming, virtual reality, and autonomous vehicles. This role involves pushing performance boundaries for all CPU products by analyzing and optimizing workloads across various markets and identifying critical application behaviors. You will work with architects to improve future CPU and system designs and benchmark NVIDIA's CPU offerings against competitors.

$224k - $431k

We are seeking a software engineer with a strong background in parallel processing and GPU architecture to advance performance at the intersection of AI, high-performance computing, and financial markets. This role involves in-depth work with parallel algorithms, GPUs, and complex systems to identify and resolve bottlenecks, maximizing the capabilities of advanced processing hardware. You will collaborate with leading experts, influence future platforms, and share your findings with the global developer community. If you excel at solving challenging technical problems, enjoy performance tuning, and want your work to significantly impact an industry, we encourage you to apply.

$152k - $288k

NVIDIA is seeking a Principal Deep Learning Communication Architect to define the long-term technical roadmap for communication libraries across next-generation platforms, ensuring seamless scaling of models to massive clusters. This role involves leading the development of advanced communication primitives and collective algorithms, optimizing for heterogeneous interconnects, and co-designing libraries with application developers to meet the demands of trillion-parameter and Agentic AI. The architect will also collaborate with silicon architects to influence hardware specifications for future networking needs and develop analytical models to predict system behavior under emerging workloads.

$272k - $431k

An applied research team within NVIDIA's Networking Systems & Software Architecture group is tackling complex AI infrastructure challenges. The team develops systems-level software to optimize data movement between GPUs, nodes, and storage at the speed required for modern AI, focusing on low-level transport, hardware-software co-design, and communication frameworks integrated into AI stacks. Their work also extends to emerging areas like quantum computing interconnects. This Principal Architect role will define the research agenda and architectural direction for NVIDIA's large-scale AI systems communication, encompassing GPUs, DPUs, NICs, and heterogeneous storage. The position demands the ability to define project scope, conduct original research, publish findings, and translate breakthroughs into production-ready software for industry-wide deployment.

$272k - $431k

NVIDIA is seeking a Software Engineering Manager for its applied research team within the Networking Systems & Software Architecture group. This role will focus on solving complex AI infrastructure challenges by building systems-level software that efficiently moves data between GPUs, nodes, and storage at the speed required for modern AI. The team's work spans low-level transport optimization, hardware-software co-design, and communication frameworks integrated into production AI stacks, with an expansion into emerging areas like quantum computing interconnects. The Engineering Manager will lead this team, driving execution and setting technical direction, while fostering an extraordinary engineering organization.

$184k - $357k

NVIDIA is seeking an outstanding research scientist to build humanoid robot foundation models and systems within the Generalist Embodied Agent Research (GEAR) group. The mission is to create general-purpose embodied agents capable of exploring and mastering complex skills in both virtual and physical environments. You will collaborate with a research team known for influential work in multimodal foundation models, large-scale robot learning, game AI, and physical simulation, contributing to significant research projects and product roadmaps, including milestones like Project GR00T, a foundation model for humanoid robots.

$192k - $357k

NVIDIA is seeking a Senior Research Engineer to join their AI Developer Tools organization. This role focuses on building AI coding agents, models, datasets, and evaluations to empower CUDA developers with AI-powered coding tools. The team operates at the forefront of AI development, working on novel coding agents, fine-tuning code LLMs, publishing benchmarks, and contributing datasets for foundation models. This position offers the opportunity to apply AI research depth to a fast-paced, shipping-oriented team, influencing new projects and collaborating with product teams to integrate research into features used by both internal and external customers.

$224k - $431k

NVIDIA is seeking a Principal Engineer to drive the performance of large-scale AI training and post-training workloads across NVIDIA’s full hardware and software stack. This role sits at the intersection of distributed training, GPU architecture, systems software, deep learning frameworks, and performance engineering. You will analyze and optimize frontier-scale LLM workloads running on thousands of GPUs, drive improvements across frameworks such as PyTorch, JAX, NeMo, and NeMo RL, and use insights from real workloads to help shape future NVIDIA GPU, system, and software roadmaps. We are looking for a deeply technical leader who can operate across abstraction layers: from application-level training behavior to framework/runtime internals, CUDA libraries, communication collectives, memory systems, networking, and GPU architecture. At this level, success means both directly improving performance directly as well as setting technical direction, raising the bar for the organization, and influencing multi-functional decisions across NVIDIA.

$272k - $431k

NVIDIA is seeking a senior or principal engineer to join the Generalist Embodied Agent Research (GEAR) group, focusing on robotics systems. This role is central to Project GR00T, an initiative to build foundation models and full-stack technology for humanoid robots. You will collaborate with a research team known for its influential work in multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation, contributing to impactful research projects and product roadmaps.

$184k - $357k

We are seeking a Senior Performance Modeling Architect to define and enhance our next-generation CPU Cache Hierarchies and interconnects. This role offers a unique opportunity to develop scalable solutions that bridge the high-reliability, low-latency requirements of Automotive systems with the efficiency and density demands of Data Center environments. You will be instrumental in creating the core models that manage data flow across our silicon, ensuring our L3/System Caches and coherent fabrics meet ambitious performance targets.

$152k - $288k

NVIDIA is seeking a GPU System Architect to design multi-GPU scale-up and scale-out systems for next-generation AI and HPC datacenter platforms. This role involves defining system architectures that integrate GPU compute, high-bandwidth memory, and interconnects to achieve industry-leading AI performance, scalability, and resilience. The ideal candidate will possess extensive experience in system-level fabric/networking architecture and hardware-software co-design.

$184k - $357k

NVIDIA is seeking a Senior AI Frameworks Engineer to join the CUTLASS team, a popular open-source ecosystem for high-performance math primitives on NVIDIA GPUs. This role focuses on developing Pythonic CUTLASS (CUTLASS DSL), aiming to bring high-performance abstractions directly into the Python environment. You will bridge the gap between low-level hardware primitives and high-level developer productivity, empowering AI researchers and engineers with better tools. If you are passionate about building elegant, high-performance DSLs, this is an opportunity to contribute to the next frontier of GPU programming.

$152k - $288k

NVIDIA BioNeMo is seeking a Senior Software Engineer to join the cuEquivariance team. This team develops and ships production GPU kernels and software interfaces that accelerate geometric neural networks on NVIDIA GPUs, enabling researchers in fields like molecular biology, materials science, and physics to train and deploy equivariant models at scale. The role involves CUDA kernel engineering, Python library development with PyTorch and JAX, and collaboration with research teams and external framework developers. This is an opportunity to work at the intersection of GPU computing and graph-based deep learning, with your work impacting scientific communities through production pipelines.

$184k - $357k

NVIDIA's CUTLASS is a popular open-source ecosystem for high-performance linear algebra and Tensor Core primitives, providing C++ and Python abstractions for computations on NVIDIA GPUs. This role focuses on bridging the gap between current and theoretical performance, optimizing GPU kernels and fusion opportunities within deep learning models. You will develop tooling for automated benchmarking and analysis, becoming an authoritative resource on kernel performance and collaborating with various NVIDIA teams.

$152k - $288k

NVIDIA is seeking a senior software engineer for its AI Networking Codesign and Benchmarking R&D group. In this role, you will be responsible for profiling, analyzing, and optimizing AI workloads on large-scale GPU and CPU clusters, focusing on distributed Deep Learning LLM training and inference. Your work will center on collective communication and networking, involving collaboration across hardware components like HCAs, Switches, CPUs, and GPUs, as well as software layers including LLM applications, machine learning frameworks, and communication libraries. You will also develop performance analysis tools and strategies to identify and clarify performance expectations, limitations, and bottlenecks, contributing directly to AI innovation.

$272k - $489k