ML Infra Engineer for Autonomous Driving

Applied Intuition; Sunnyvale (CA); On-site; USD 153,000 - 222,000; Full time

Job summary

Applied Intuition is shaping the future of autonomous driving by building ML tools and infrastructure for large-scale end-to-end autonomy research. You will work with AI research and engineering teams to productionize cutting-edge self-driving software and help scale training pipelines as data and compute needs grow.

The role emphasizes ownership, collaboration with internal and external users, and a pragmatic, fast-paced culture focused on delivering reliable autonomous software solutions.

Qualifications

• Exceptional software generalist with ambition to contribute up and down the ML stack, onboard the vehicle, and in the cloud.
• Strong fundamental skills in software & module design: can tame chaos with libraries & abstractions.
• Rapid analytical and problem-solving skills.

Responsibilities

• Build tools and infrastructure to enable large-scale E2E autonomy research led by Dr. Wei Zhan.
• Work directly with AI research and engineering teams to productionize next generation self-driving software.
• Help scale end-to-end training by identifying bottlenecks in GPU compute, on-road data, curation, and eval systems.

Skills

Software generalist

Module design

Analytical skills

Python

PyTorch

CUDA

Bazel

Kubernetes

Spark

Flyte

Tools

Virtual Machines

Docker

Kubernetes

Job description

Applied Intuition is shaping the future of autonomous driving by building ML tools and infrastructure for large-scale end-to-end autonomy research. You will work with AI research and engineering teams to productionize cutting-edge self-driving software and help scale training pipelines as data and compute needs grow.

The role emphasizes ownership, collaboration with internal and external users, and a pragmatic, fast-paced culture focused on delivering reliable autonomous software solutions.