Senior Research Engineer - AI Coding Tools

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Research Engineer at NVIDIA focused on building and improving AI coding agents, fine-tuning code LLMs, designing evaluations, and developing interfaces for AI agents to interact with NVIDIA's developer tools. The role involves shipping novel agents and features, contributing to benchmarks, and generating synthetic data for AI-for-code applications.

What you'd actually do

  1. 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
  2. Design and ship evaluations, including extensions of our public ComputeEval benchmark, that measure what really matters in AI-powered CUDA development
  3. Fine-tune and specialize code LLMs, and partner with the Nemotron team on the datasets and evaluations that feed NVIDIA's foundation models
  4. 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
  5. Generate, curate, and validate synthetic training and evaluation data for CUDA programming

Skills

Required

  • Python
  • sound software engineering practices
  • fine-tuning or evaluating LLMs
  • systems side of LLM-powered agents
  • context management
  • prompt caching
  • tool-use design
  • MCP
  • Agent Skills
  • designing or contributing to rigorous evaluations for code generation or agentic systems

Nice to have

  • B.S. in Computer Science or related technical field or equivalent experience
  • M.S. or Ph.D.
  • public contributions in the AI-for-code space
  • open-source agents or tools
  • widely-used benchmarks
  • influential papers
  • blog posts with demonstrated real-world impact
  • building coding agents or code LLMs that real users rely on every day
  • CUDA or other GPU programming
  • NVIDIA profiling tools (Nsight Compute, Nsight Systems)
  • libraries (cuDNN, cuBLAS, Thrust, CUB)
  • synthetic data generation and quality validation for code
  • zero-to-one product work
  • work inside a recently-rebooted org with a strong mandate and customer pull

What the JD emphasized

  • meaningful recent work in the AI-for-code space
  • Track record of shipping
  • comfortable in a small, collaborative, in-person team with fast direction changes and little process overhead

Other signals

  • AI coding agents
  • code LLMs
  • AI developer tools
  • shipping AI coding tools