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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. The AI coding space is moving faster than any of us have seen — products rise and fall in months — and we work on it from the epicenter: the company whose hardware most of the AI industry runs on. 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. The space shifts every few weeks, and we move with it. In this role, you'll bring applied AI research depth to a team that values shipping as much as experimentation. You won't be filling a narrow gap — 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. For experienced AI-for-code practitioners who want to do frontier applied work with the stability and resources of NVIDIA behind them, this is a rare seat. What You'll Be Doing 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 What We Need To See 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 Ways To Stand Out From The Crowd Public contributions in the AI-for-code space — open-source agents or tools, widely-used benchmarks, influential papers, or blog posts with demonstrated real-world impact Experience building coding agents or code LLMs that real users rely on every day Familiarity with CUDA or other GPU programming, and/or with NVIDIA profiling tools (Nsight Compute, Nsight Systems) and libraries (cuDNN, cuBLAS, Thrust, CUB) Experience with synthetic data generation and quality validation for code Track record of zero-to-one product work, or work inside a recently-rebooted org with a strong mandate and customer pull With competitive salaries and benefits, 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 an applied AI researcher or engineer who wants to ship AI coding tools from the epicenter of the AI industry, and you thrive in a small, in-person team with a clear mandate, this is the role for 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 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until May 4, 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. , , JR2017020
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.