Senior High-Performance LLM Training Engineer

NVIDIA; Santa Clara (CA); On-site; USD 184,000 - 356,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior High-Performance LLM Training Engineer to enhance the efficiency of LLM training workloads. Focused on optimizing NVIDIA's software stack in frameworks such as PyTorch and JAX, this role entails working with advanced GPU technologies.

The ideal candidate should possess a PhD or equivalent degree with substantial experience in deep learning, GPU architecture, and performance optimization. The base salary ranges between 184,000 USD and 356,500 USD based on experience and position level.

Qualifications

• PhD or MS in relevant fields with extensive work experience.
• Strong deep learning and neural network background.
• Experience in performance analysis and tuning applications.

Responsibilities

• Optimize NVIDIA's high-performance LLM software stack.
• Implement software in deep learning platforms like PyTorch and JAX.
• Build tools for workload optimization and analysis.

Skills

Deep learning

Neural networks

Performance analysis

Optimization

GPU architecture

C++

Python

CUDA

Education

PhD in Computer Science, Electrical Engineering or Computer Engineering

MS or equivalent experience

Job description

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 & system-level performance modeling.
• Programming skills in C++, Python, and CUDA.

#LI-Hybrid

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.

Applications for this job will be accepted at least until April 12, 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.