Staff ML Engineer: Imitation Learning for Autonomous Driving

General Motors LLC; Sunnyvale (CA); Remote; USD 189,000 - 280,000; Full time

Benefits offered by this job

Health benefits

Relocation assistance

Job summary

General Motors is hiring a Staff Software/ML Engineer to join the Embodied AI IL team in California. You will architect modular ML software for data preparation, training, evaluation, and production integration, while optimizing end-to-end training and gaining fast feedback on model quality.

You’ll lead cross-team initiatives, mentor engineers, and improve software reliability, with strong Python and PyTorch skills and experience in RL, distributed training, and production ML systems.

Qualifications

• Master’s or PhD degree in Computer Science, a related field, or equivalent practical experience.
• Track record of leading complex software projects and delivering hands-on implementation across team boundaries.
• Strong Python skills and experience building maintainable, well-tested software in large codebases.
• Hands-on experience with PyTorch or comparable frameworks and ML training/evaluation systems.
• Experience profiling and optimizing performance-sensitive ML pipelines, including data processing, CPU/GPU execution, and distributed training.
• Strong technical judgment and ability to translate research needs into reliable production software.

Responsibilities

• Architect ML software spanning data preparation, training, evaluation, and production integration.
• Optimize end-to-end training/evaluation performance, including data loading and distributed execution.
• Lead cross-team initiatives, mentor engineers, and improve software reliability.

Skills

Python

PyTorch

Distributed training

Software architecture

Mentoring

Education

Master's or PhD in Computer Science or related

Tools

C++

GPU profiling

ML runtime

Job description

General Motors is hiring a Staff Software/ML Engineer to join the Embodied AI IL team in California. You will architect modular ML software for data preparation, training, evaluation, and production integration, while optimizing end-to-end training and gaining fast feedback on model quality.

You’ll lead cross-team initiatives, mentor engineers, and improve software reliability, with strong Python and PyTorch skills and experience in RL, distributed training, and production ML systems.