Role at a glance
- Salary
- $168K – $327.8K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 7+ years of technical product management or closely related experience
- Education
- BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Product Manager will lead AI agent and LLM-based coding workflows that generate, refactor, and optimize CUDA kernels and graph-level execution plans. The role spans data pipelines, evaluation suites, GPU-accelerated runtimes, and the broader agent lifecycle to support the release of faster inference and training solutions.
What You'll Do
- Architect agent-focused products for generating, refactoring, and optimizing CUDA kernels and graph-level execution plans across GPU...
- Define the end-to-end data lifecycle for agent training and evaluation, including dataset curation, artificial data creation, and...
- Partner with CUDA, kernel, and compiler engineering teams to integrate agents with compilers, profilers, execution sandboxes, and runtimes
- Collaborate with developers, NVIDIA leaders, and ecosystem partners to drive multi-agent orchestration
- Prioritize features and deliver launches and messaging for agentic AI kernel generation
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; experience in the AI agent or LLM space, including developing or productizing coding agents; experience with multi-agent orchestration, self-healing or code loops, and connecting agents to compilers or execution environments; experience crafting and releasing automated testing or evaluation suites measuring correctness, performance, and latency; BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems.
Required
- Technical product management or closely related experience
- Shipping developer or platform products in AI, ML infrastructure, or high-performance computing
- AI agent or LLM experience, including developing or productizing coding agents
- Multi-agent orchestration
- Self-healing or code loops that improve over time
- Connecting agents to compilers or execution environments
- Automated testing or evaluation suites measuring correctness, performance, and latency
- BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing...
Preferred
- PhD or equivalent experience in Computer Engineering, Computer Science, or another technical specialty
- Building or launching coding-agent platforms or copilots used by development teams at scale
- Contributions to performance-critical open-source projects with clear community adoption and impact
- Research experience in GPU kernel optimization, collective or group communication algorithms, multi-agent systems, or ML model serving /...
- Crafting cost-per-inference or cost-per-token models incorporating hardware utilization, energy efficiency, and cluster scaling
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA's AI Software Platforms team is building the next generation of agentic AI infrastructure that lets coding agents synthesize, optimize, and deploy GPU kernels automatically. This job focuses on crafting AI kernels that connect data pipelines, evaluation suites, and GPU-accelerated runtimes. This helps developers safely release faster, better-performing inference and training solutions.
As Product Managers at NVIDIA, we enable developers to be successful on the NVIDIA platform and push the boundaries of what is possible with AI deployments. In this role, you will act as the internal champion for AI agents and LLM-based coding workflows that generate optimized kernels. You'll partner closely with engineering, research, and customers to define strategy, develop roadmaps, and build products that span the entire agent lifecycle — from data collection and synthetic data generation to evaluation, deployment, and continuous improvement.
What you'll be doing:
We architect agent-focused products that let coding agents generate, refactor, and optimize CUDA kernels and graph-level execution plans across diverse GPU architectures.
Define the end-to-end data lifecycle for agent training and evaluation, including dataset curation, artificial data creation, and benchmark suites for correctness, latency, and adaptability.
Partner with CUDA, kernel, and compiler engineering teams to integrate agents with compilers, profilers, execution sandboxes, and runtimes in a safe, observable way.
We collaborate with internal and external developers, NVIDIA leaders, and ecosystem partners to drive multi-agent orchestration, prioritize features, and deliver launches and messaging for agentic AI kernel generation.
What we need to see:
7+ years of technical product management or closely related experience shipping developer or platform products in AI, ML infrastructure, or high-performance computing; we care deeply about end-to-end ownership and impact.
Proven experience in the AI agent or LLM space, including developing or productizing coding agents. Experience with multi-agent orchestration and self-healing or code loops that improve over time is required. Candidates should also have worked on connecting agents to compilers or execution environments.
Proven record of crafting and releasing automated testing or evaluation suites. These suites measure agents on non-subjective metrics such as correctness, performance, and latency. We rely on data to guide both development and iteration.
BS or MS in Computer Engineering, Computer Science, or a related technical field, or equivalent experience in parallel computing architectures and systems.
Ways to stand out from the crowd:
PhD or equivalent experience in Computer Engineering, Computer Science, or another technical specialty.
Track record building or launching coding-agent platforms or copilots used by development teams at scale, and contributions to performance-critical open-source projects (e.g., Triton, TVM, FlashAttention, kernel libraries, agent frameworks) with clear community adoption and impact.
Research experience in GPU kernel optimization, collective or group communication algorithms, multi-agent systems, or ML model serving / inference architectures that shows how you think about systems end-to-end.
Experience crafting cost-per-inference or cost-per-token models that incorporate hardware utilization, energy efficiency, and cluster scaling, and using those models to guide product strategy and tradeoffs.
You will also be eligible for equity and benefits.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.