Senior High-Performance LLM Training Engineer
NVIDIA is hiring a Senior High-Performance LLM Training Engineer in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions PyTorch and JAX among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
We are now looking for a Senior High-Performance LLM Training Engineer!
NVIDIA is seeking experienced engineers specializing in performance analysis and optimization to improve the efficiency of LLM training workloads, which are shaping the world's most advanced computing systems. This position focuses on optimizing NVIDIA’s high-performance LLM software stack in frameworks like PyTorch and JAX for high-performance training on thousands of GPUs, while also helping shape hardware roadmaps for the next generation of GPUs powering the AI revolution.
What you will be doing:
Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms.
Understand the big picture of training performance on GPUs, prioritizing and then solving problems across all state-of-the-art neural networks.
Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
Build and support NVIDIA submissions to the MLPerf Training benchmark suite.
Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
Build tools to automate workload analysis, workload optimization, and other critical workflows.
What we want to see:
PhD in Computer Science, Electrical Engineering or Computer Engineering and 5+ years; or MS (or equivalent experience) and 8+ years of meaningful work experience.
Strong background in deep learning and neural networks, in particular training.
A deep background in computer architecture and familiarity with the fundamentals of GPU architecture.
Proven experience analyzing and tuning application performance & processor and system-level performance modelling.
Programming skills in C++, Python, and CUDA.
GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with the major systems companies and every major cloud service provider to make GPUs available in data centers and in the cloud. We craft computers and software to bring AI to edge devices, such as self-driving cars and autonomous robots. AI has the potential to spur a wave of social progress unmatched since the industrial revolution.
Widely considered to be one of tech's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Additionally, this opportunity offers you the ability to collaborate with some of the most forward-thinking and hard-working people in the world, shaping the future of AI in a creative and autonomous work environment that encourages innovation. If you're excited to work across the full hardware & software stack—from GPU architecture to application code—to achieve optimal performance, we want to hear from you!
#LI-Hybrid
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: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.
Applications for this job will be accepted at least until November 3, 2026.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.How we rate this
Senior High-Performance LLM Training Engineer at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used JAX in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch and JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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