ML Inference & Compiler Engineer (Accelerators)

Google DeepMind; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google DeepMind is building a next-generation compute platform for AI inference workloads, with memory tech, HW acceleration, and SW/HW codesign. We seek engineers who take initiative to advance ML compiler stack and inference infrastructure, joining a team that directly impacts AI development for Google and industry.

This is a coding role for engineers who enjoy hands-on work, collaboration, and delivering high-performance software.

Qualifications

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• Experience in software development using Python and C++.
• Experience with ML hardware accelerators, ML compiler stacks (e.g., JAX, PyTorch, XLA), and kernel development.

Responsibilities

• Direct full-stack Software role focusing on ML compiler and inference infrastructure.
• Design and develop ML compiler stack to bridge AI workloads and low-level Hardware operators.
• Design and develop SW infrastructure to enable high performance inference.
• Drive SW/HW codesign, kernel optimization, performance tuning, and debugging.

Skills

Python

C++

ML accelerators

ML compilers

Kernel development

Education

Bachelor's degree in Computer Science, related field, or equivalent practical experience

PhD degree in Computer Engineering/CS (preferred)

Tools

JAX

PyTorch

XLA

Job description

Google DeepMind is building a next-generation compute platform for AI inference workloads, with memory tech, HW acceleration, and SW/HW codesign. We seek engineers who take initiative to advance ML compiler stack and inference infrastructure, joining a team that directly impacts AI development for Google and industry.

This is a coding role for engineers who enjoy hands-on work, collaboration, and delivering high-performance software.