Staff ML Engineer - Embodied AI Scaling Foundations

About the role

The Data Scaling team at General Motors is responsible for developing and refining machine learning models for autonomous vehicles (AVs). This team focuses on maximizing the data used for model training, ensuring high-quality data across various sources, and delivering models that enhance the safety and reliability of GM's autonomous driving technologies.

Responsibilities

• Design and implement ML solutions that leverage large-scale foundation models and alignment methods to improve AV performance.
• Collaborate with cross-functional teams to deploy ML models into onboard driving systems.
• Contribute to applied research efforts and stay updated with advancements in ML frameworks and methods.
• Build and scale model training pipelines to enable efficient iteration across teams.
• Design and build efficient infrastructure, pipelines, and tooling to facilitate fast-paced model iterations.
• Drive technical execution from prototyping through production deployment, documenting learnings and best practices.
• Support and mentor engineers through technical collaboration and code reviews.

Requirements

Experience working with large-scale foundation models and alignment methods applied to real-world systems. Demonstrated ability to deliver applied ML solutions under real-world constraints and timelines. Proficiency in PyTorch and Python. Experience building and scaling model training pipelines enabling efficient iteration across teams. Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark. Strong communication skills enabling effective collaboration across engineering teams. Experience deploying ML models into production environments and understanding end-to-end deployment workflows. Experience in robotics or autonomous driving systems preferred.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Machine Learning, or related field.

Skills & Abilities

• Experience working with large-scale foundation models and alignment methods applied to real-world systems.
• Demonstrated ability to deliver applied ML solutions under real-world constraints and timelines.
• Proficiency in PyTorch and Python.
• Experience building and scaling model training pipelines enabling efficient iteration across teams.
• Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark.
• Strong communication skills enabling effective collaboration across engineering teams.
• Experience deploying ML models into production environments and understanding end-to-end deployment workflows.
• Experience in robotics or autonomous driving systems preferred.

Benefits

• Health and wellbeing benefit programs including medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts.

Pay

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area. The salary range for this role is $189,000 to $300,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Schedule

This role is categorized as fully remote or hybrid.