Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 8
Agentic Systems @ 4
CUDA
Experimentation
LLM @ 6
Machine Learning
Python @ 7
RAG @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA's AI Developer Tools organization is seeking a Senior Research Engineer to join our Research team, where we build the AI coding agents, models, datasets, and evaluations at the heart of NVIDIA's strategy to put AI-powered coding tools in the hands of every CUDA developer.
Our team is small, in-person, and high-velocity. We prototype and ship novel coding agents, fine-tune and evaluate code LLMs, publish benchmarks like ComputeEval, and contribute datasets that feed NVIDIA's Nemotron foundation models. We make NVIDIA's core developer tools—including Nsight Compute and Nsight Systems—first-class citizens for AI agents through MCP servers and Agent Skills.
In this role, you’ll bring applied AI research depth to a team that values shipping as much as experimentation. You’ll pick up significant projects across our portfolio, help set direction on new ones, and partner closely with product teams turning our research into features used by NVIDIA developers and external customers.
Responsibilities
- Build and improve novel coding agents that help NVIDIA developers write, optimize, and maintain CUDA code—and that work alongside other AI agents in the developer's workflow
- Design and ship evaluations, including extensions of our public ComputeEval benchmark, that measure what really matters in AI-powered CUDA development
- Fine-tune and specialize code LLMs, and partner with the Nemotron team on the datasets and evaluations that feed NVIDIA's foundation models
- Develop Agent Skills, MCP servers, and other tool-use interfaces that make NVIDIA's developer tools (Nsight Compute, Nsight Systems, and more) first-class for AI agents
- Generate, curate, and validate synthetic training and evaluation data for CUDA programming
- Deliver "net new knowledge" to frontier LLMs through RAG and skill-based systems that keep models current with NVIDIA's fast-moving software stack
- Collaborate with partner product teams to turn research prototypes into shipping features used inside NVIDIA and by external customers
Requirements
- B.S. in Computer Science or related technical field or equivalent experience (M.S. or Ph.D. a plus)
- 12+ years of industry experience in applied AI/ML, with meaningful recent work in the AI-for-code space—coding agents, code LLMs, AI developer tools, or adjacent systems
- Strong proficiency in Python and sound software engineering practices
- Hands-on experience fine-tuning or evaluating LLMs, with appropriate humility about the complexity of training and data work
- Fluency with the systems side of LLM-powered agents, including practical concerns like context management, prompt caching, tool-use design, MCP, and Agent Skills
- Experience designing or contributing to rigorous evaluations for code generation or agentic systems
- Track record of shipping—taking work past the prototype stage and into the hands of real users
- Comfortable in a small, collaborative, in-person team with fast direction changes and little process overhead
Benefits
- You will also be eligible for equity and benefits.