High-Performance LLM Training Engineer - New College Grad 2027

at Nvidia

📍 Santa Clara, United States

USD 124,000-241,500 per year

JUNIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 CUDA @ 3 Deep Learning @ 6 GPU @ 2 JAX LLM Performance Analysis PyTorch Python @ 3 Robotics

Details

GPU computing is a pervasive platform for deep learning and artificial intelligence. NVIDIA integrates and optimizes deep learning frameworks and develops systems and software for data centers, cloud environments, edge devices, autonomous vehicles, and robotics.

NVIDIA is seeking a High-Performance LLM Training Engineer to specialize in performance analysis and optimization for large language model training workloads. The role focuses on optimizing NVIDIA's high-performance LLM software stack in frameworks such as PyTorch and JAX for pre-training and post-training on thousands of GPUs. The engineer will also help shape hardware roadmaps for future GPU architectures.

Responsibilities

Understand, analyze, profile, and optimize AI training workloads on innovative hardware and software platforms.
Analyze overall GPU training performance and prioritize and solve problems across state-of-the-art LLMs.
Implement production-quality software across multiple layers of NVIDIA's deep learning platform stack.
Implement key LLM training workloads in NVIDIA's proprietary processor and system simulators to support future architecture studies.
Build agentic tools to automate workload analysis, workload optimization, and other critical workflows.

Requirements

M.S. or Ph.D. in Computer Science, Electrical Engineering, or Computer Engineering, or equivalent experience.
Strong background in deep learning and neural networks, particularly model training optimization.
Deep background in computer architecture and familiarity with GPU architecture fundamentals.
Proven experience analyzing and tuning application performance, as well as processor- and system-level performance modeling.
Programming skills in C++, Python, and CUDA.

Benefits

Base salary range of $124,000–$195,500 for Level 2.
Base salary range of $152,000–$241,500 for Level 3.
Equity and benefits.
NVIDIA states that it offers a comprehensive benefits package.

Applications will be accepted at least until October 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.