Staff ML/RL Engineer - AV Simulation & Pipelines

Aimlroles; Northern (KY); Hybrid; USD 145,000 - 284,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Retirement savings plan

Paid vacation

Job summary

General Motors is seeking a seasoned ML/RL engineer to advance models and systems for autonomous vehicle simulations, training pipelines, and production deployment. The role emphasizes scalable architectures, cross-functional collaboration with perception and safety teams, and hands-on SWE contributions in a hybrid remote setting.

The candidate should bring 4+ years in robotics or latency-sensitive backend services, strong C++/Python skills, and experience with TensorFlow or PyTorch.

Qualifications

• 4+ years of experience in robotics or latency-sensitive backend services.
• Experience with ML frameworks such as TensorFlow or PyTorch.
• Experience building highly performant ML and system pipelines.
• Strong programming skills in modern C++ or Python.

Responsibilities

• Support the team in developing machine learning (ML) and reinforcement learning (RL) models, including training loop development and optimization.
• Streamline integration and create ML infrastructure, metrics, and data pipelines for production model deployment and rapid experimentation.
• Work as part of an ML team and contribute strong software engineering (SWE) expertise.
• Support the ML team in accelerating project timelines, particularly in areas related to Autopilot, Lane Keep, and autonomous vehicle (AV) technologies.
• Experience in simulation and robotics is highly desirable, with a preference for candidates from AV or robotics backgrounds rather than solely cloud-focused companies.

Skills

C++

Python

ML/RL

Latency-sensitive backend

Profiling performance

RL/ML models

Tools

TensorFlow

PyTorch

Profiling tools

Job description

General Motors is seeking a seasoned ML/RL engineer to advance models and systems for autonomous vehicle simulations, training pipelines, and production deployment. The role emphasizes scalable architectures, cross-functional collaboration with perception and safety teams, and hands-on SWE contributions in a hybrid remote setting.

The candidate should bring 4+ years in robotics or latency-sensitive backend services, strong C++/Python skills, and experience with TensorFlow or PyTorch.