2027 Summer Intern, MS/PhD, AI-driven ML Performance Engineering Intern

Highlights

• Build high-performance low-level kernels for Waymo's custom ML accelerator.
• Develop a harness that recursively improves kernel generation without human input.
• Power the Waymo Driver behind 10M+ rider-only trips and 100M autonomous miles.

What they offer

• Generous benefits programs

Ideal candidate

An MS or PhD student obsessed with AI-assisted coding who loves squeezing maximum performance from custom silicon to advance autonomous driving.

Requirements

• Currently enrolled in MS or PhD program in Computer Science, Computer Engineering, Computational Science or related quantitative field
• Demonstrated track record using AI agents and harnesses to improve coding performance
• Working knowledge of key kernels for transformer inference including performance analysis and optimization
• Familiarity with low-level ML accelerator DSLs such as CUDA, Triton, Gluon, etc.
• Solid understanding of modern inference accelerator architectures
• Fluency in Python and/or C++
• Working knowledge of ML numerical formats and accuracy vs performance tradeoffs