High-Performance LLM Training Engineer

What you'll do

• Analyze and profile AI training workloads on innovative hardware and software platforms.
• Optimize high-performance LLM training workloads across thousands of GPUs.
• Implement production-quality software across multiple layers of the deep learning platform stack.
• Execute key LLM training workloads in proprietary processor and system simulators.
• Build agentic tools to automate workload analysis and optimization workflows.
• Solve performance problems for state-of-the-art large language models.
• Provide input to shape hardware roadmaps for next-generation GPUs.

What we're looking for

• M.S. or PhD in Computer Science, Electrical Engineering, or Computer Engineering (or equivalent experience).
• Strong background in deep learning and neural networks, specifically model training optimizations.
• Deep background in computer architecture and familiarity with the fundamentals of GPU architecture.
• Proven experience analyzing and tuning application performance and processor/system-level performance modeling.
• Programming skills in C++, Python, and CUDA.
• Experience optimizing LLM training workloads in frameworks like PyTorch and JAX.