Lead AI Infrastructure Engineer

The role

You will focus on the GPU inference framework and performance. You will later take ownership of broader ML infrastructure across ML pipelines.

What you will do

• Take on the GPU inference framework, focusing on performance
• Assume responsibility and ownership for broader ML infrastructure scattered across ML pipelines
• Collaborate with the applied ML team to define neural model architecture

Required qualifications

• Experience with PyTorch
• Understanding of how GPUs work
• Experience in diagnosing and resolving performance issues
• Strong record of building infrastructure including distributed systems
• 5+ years of experience with C++
• Programming experience in multi-threaded environments - multiple processes, threads, timers, and interrupts
• Authorized to work in the U.S.

About the company

Avride's team builds the base infrastructure layer that powers the self-driving stack. This includes a C++ framework for autonomy components, execution graph building and optimization systems, and runtimes.