ML Inference & Accelerator Software Engineer

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

Benefits offered by this job

Equity

Benefits

Job summary

Google DeepMind in San Francisco is seeking engineers for a direct full-stack software role focusing on ML compiler stack and inference infrastructure. You will design and develop the ML compiler stack to bridge AI workloads and low-level hardware operators, and build SW infrastructure for high-performance inference.

Join a team of researchers and engineers tackling next-generation compute platforms for AI, with equity, benefits, and a 15% bonus target.

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 machine learning (ML) hardware accelerators, ML compiler stacks (e.g., JAX, PyTorch, XLA), and kernel development.

Responsibilities

• Direct full-stack Software (SW) role, focusing on ML compiler and inference infrastructure.
• Design and develop ML compiler stack to bridge AI workloads and low-level Hardware (HW) 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 compiler stacks

Kernel development

Education

Bachelor's degree in CS or related

PhD degree (preferred)

Tools

JAX

PyTorch

XLA

Job description

Google DeepMind in San Francisco is seeking engineers for a direct full-stack software role focusing on ML compiler stack and inference infrastructure. You will design and develop the ML compiler stack to bridge AI workloads and low-level hardware operators, and build SW infrastructure for high-performance inference.

Join a team of researchers and engineers tackling next-generation compute platforms for AI, with equity, benefits, and a 15% bonus target.