Senior ML Engineer - Embodied AI Scaling Foundations
General Motors2 days ago
Base Salary
$159k - $231k/yr
Responsibilities
- Design and run experiments involving dataset mixtures, sampling strategies, curricula, and scaling-law studies.
- Apply self-supervised pre-training, imitation learning, reinforcement learning, and foundation-model fine-tuning to driving behavior, trajectory generation, and perception.
- Develop data curation and mining methods including auto-labeling, deduplication, uncertainty estimation, and long-tail and out-of-distribution scenario discovery.
- Define offline metrics and evaluations that predict on-road behavior and guide model and data decisions.
- Trace model failures to their data root causes and specify corrective data requirements.
- Train models at scale across large multi-GPU and multi-node datasets while partnering with platform teams on required pipelines and tooling.
- Collaborate with cross-functional teams to bring models into onboard driving systems and document learnings and best practices.
- Follow relevant literature and incorporate promising advances into training recipes and evaluations.
Requirements
- Master's or PhD in Computer Science, Robotics, or Machine Learning.
- Strong machine learning fundamentals, including experimental design, baseline selection, ablation analysis, and interpreting signal versus noise.
- Proficiency in Python and PyTorch, with experience training models on large datasets.
- Hands-on experience with data-centric ML, including curation, sampling, labeling, or evaluation of large training sets.
- Working knowledge of large-scale foundation-model pre-training, fine-tuning, and alignment.
- Data analysis skills using NumPy and Pandas, plus SQL or Spark for large datasets.
- Demonstrated ability to deliver applied ML results under real-world constraints and timelines.
- Ability to communicate results and limitations to engineers and non-experts.
- Preferred qualifications include a PhD, publications, or open-source contributions in representation learning, multimodal or vision-language models, generative models, reinforcement learning, or data-centric ML.
- Experience with robotics, autonomous driving, embodied AI systems, synthetic or simulation data, sim-to-real transfer, or production ML deployment is preferred.
Benefits
- Fully remote or hybrid work arrangement.
- Health, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings, sickness and accident benefits, life insurance, paid vacation and holidays, tuition assistance, employee assistance program, and GM vehicle discounts.
- Potential eligibility for relocation benefits.
- Bonus potential through an incentive pay program based on company performance, job level, and individual performance.
Tech Stack
Categories
ML EngineeringRobotics
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.