Senior High Performance AI Engineer
Free to start · No card · 5 credits the moment you sign up
Job description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are looking for outstanding Senior High Performance AI Engineer to build groundbreaking multi-agent systems for the CUDA ecosystem. We build innovative agentic runtimes and compiler-integrated orchestration that work together with NVIDIA's software stack to provide comprehensive acceleration for modern agent workloads powered by foundational models. As a member of the team, you will develop new agent abstractions, GPU-centric runtimes, and compiler- or runtime-driven system solutions to accelerate agent planning, tool-use, code generation, and other high-impact AI workloads. You will collaborate closely with internal NVIDIA software and hardware teams to push the latest developments into NVIDIA products.
What you'll be doing:
- Design, build and optimize agentic AI systems for the CUDA ecosystem.
- Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available.
- Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity.
- Collaborate across the AI stack—from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving—and with model/agent teams.
What we need to see:
- Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD preferred.
- 8+ years of industry or academia experience with AI systems development; exposure to building foundational models, agents or orchestration frameworks; hands-on experience with deep learning frameworks and modern inference stacks.
- Strong C/C++ and Python programming skills; solid software engineering fundamentals.
- Experience with GPU programming and performance optimization (CUDA or equivalent).
Ways To Stand Out From The Crowd:
- Track record building/evaluating deep learning models, coding agents and developer tooling.
- Demonstrated ability to optimize and deploy high-performance models, including on resource-constrained platforms.
- Deep expertise in GPU performance optimizations, evidenced by benchmark wins or published results.
- Publications or open-source leadership in deep learning, multi-agent systems, reinforcement learning, or AI systems; contributions to widely used repos or standards.
With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from 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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.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 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.Originally posted on Himalayas
Prepare your application
Use the description above to assess your fit for NVIDIA. This checklist is guidance from Resumize, rather than additional requirements from the employer. Imported listings can be shortened or change after collection, so confirm the complete description and current availability before sending an application.
Match requirements to evidence
Identify the responsibilities and skills the employer explicitly names. For each important requirement, choose one example from your work, education, training, or projects. Explain what you did, how you did it, and what changed as a result. Include a measurable outcome when you can support it. If you lack a requirement, describe related experience accurately instead of adding an unfamiliar skill to your resume.
Put the most relevant examples near the top of your resume. Keep job titles, dates, qualifications, and contact details consistent across your application materials. Use the employer’s terminology when it describes your experience accurately; a copied list of keywords does not explain your contribution. A short, specific bullet is easier to review than a paragraph that mixes several unrelated duties.
Check the working arrangement
Confirm the location, schedule, employment type, and any eligibility requirements on the employer’s site. A remote label does not establish worldwide eligibility or flexible hours. If compensation, benefits, equipment, travel, or contract duration are missing from this listing, write down your questions for the recruiter. Do not assume details from another opening at the same company apply to this role.
Review before submitting
Follow the employer’s requested file format and application instructions. Open your exported resume and check that its text is selectable, its sections read in order, and its links work. Proofread names, dates, and contact information. Share confidential work samples only when you have permission, and use an anonymized example when necessary.
Submit through a trusted employer or recruiting destination. If the original listing has disappeared, search the employer’s careers page for the title rather than assuming the vacancy remains open. Save the application date, job reference, and the version of your resume you sent. Those details help you prepare for a later conversation and avoid submitting conflicting information through several job boards.
Review your resume for writing and readability feedback, or browse other openings if this opportunity is unavailable.