Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
The Data Scaling team owns the Data Flywheel for AV Foundation model development and successive fine tuning. It defines the composition of the data that is needed for the AV to learn behaviors at scale and deliver the driving behaviors necessary for the product success. The team owns the definition and processes for data quality across the data loop.
The team directly works on and delivers ML models to the product that successively go up the Data Scaling curves, thereby directly impacting AV product performance through smart use of data. As part of this work, the team builds scalable systems and pipelines that attempt to 10x the data used, its diversity and impact on the models with successive major releases. The team uses existing very large datasets that GM has access to internally as well as defines the next generation of highest value datasets that GM continues to collect - both from real driving by GM and retail fleets, but also synthetic sim-based datasets.
Why Join Us?

• Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity - into billions+ of examples - across different sources, delivering the maximum value to the model through every additional example.
• Work with cutting-edge technology and a collaborative, high-impact team of AI/ML engineers, data scientists and engineers who are passionate about leveraging advanced AI techniques to drive innovation for L2, L3 and L4 applications.
• Contribute to the safety, reliability, and scalability of next-generation autonomous vehicles.

As a Senior AI/ML Engineer in the Embodied AI Data Foundations organization, you will develop and deploy machine learning solutions maximally leveraging multiple sources of data including real and synthetic datasets, directly impacting autonomous driving performance. You will contribute to designing and improving ML models that go up the data scaling curves and when deployed, support safe and reliable vehicle behavior across real-world scenarios.
You will collaborate closely with senior engineers and cross-functional teams to translate research and technical concepts into production-ready solutions while contributing to engineering best practices and delivery execution.
What You'll Do

• Develop and improve ML solutions aligned with GM's autonomous driving objectives.

• Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling/selection, foundation modeling, to solve problems in object detection/tracking/classification, trajectory generation, and safe AI.

• Collaborate with cross-functional teams to deploy models into onboard driving systems.

• Implement and evaluate models, incorporating research advancements into practical applications.

• Contribute to taking ML solutions from experimentation through deployment and production support.

• Participate in code reviews, documentation, and technical discussions to support engineering quality and knowledge sharing.

Your Skills & Abilities

• Bachelor's or Master's degree in Computer Science, Robotics, Machine Learning, or related field.

• Experience applying machine learning techniques to real-world systems or large-scale datasets.

• Proficiency in PyTorch and Python.

• Experience working with model training pipelines or large-scale data processing workflows.

• Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark.

• Ability to collaborate effectively within cross-functional engineering teams.

• Experience deploying ML models into production or working within production ML environments preferred.

Remote/Hybrid: This role is categorized as fully remote or hybrid.
Compensation : 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 $159,300.00 to $230,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits:

• GM offers a variety of health and wellbeing benefit programs. Benefit options include 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 and more.

This job may be eligible for relocation benefits.
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