Senior Machine Learning Engineer

General Motors; Mountain View (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

A leading company in the automotive sector is seeking a Machine Learning Engineer to join their Smart Agents group. This role involves developing ML models to simulate road users for autonomous vehicle training. Candidates should have strong software engineering skills and experience in simulation or robotics, focusing on applied machine learning. The position is remote, with occasional on-site requirements for those near specific locations.

Qualifications

• Strong software engineering skills with a focus on applied ML.
• Experience in simulation and robotics is highly desirable.

Responsibilities

• Develop ML and RL models, including training loop development and optimization.
• Create ML infrastructure, metrics, and data pipelines for production deployment.
• Support ML team in accelerating project timelines related to AV technologies.

Skills

Machine Learning

Reinforcement Learning

Software Engineering

Simulation

Robotics

Job description

Remote:

This role is based remotely, but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford, or Mountain View, you are expected to report to that location at least three times a week.

Role:

The Smart Agents group is responsible for building ML models and systems to simulate road users in various situations, generating scenarios for testing and training autonomous vehicle (AV) driving policies. Think of simulation as a video game that our AVs train on; our team develops ML/AI models that control other characters in the simulation — such as vehicles, bikers, and pedestrians — to interact realistically. Our technology stack includes Generative AI models (like GPT) and Reinforcement Learning (RL) policies. The team collaborates closely with Simulation, Behaviors, Perception, and Safety Engineering teams.

The specific duties include ML/RL model development, training loop development, optimization, integration, and creating ML infrastructure, metrics, and data pipelines for both production deployment and rapid experimentation. This team plays a critical role in testing and training our autonomous vehicles.

What You'll Do:

• Develop 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 deployment and fast experimentation.
• Contribute as a full-stack Machine Learning Engineer (MLE) with strong software engineering (SWE) skills, focusing on applied ML.
• Support the ML team in accelerating project timelines, especially in areas related to Autopilot, Lane Keep, and 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.