Staff AI/ML Engineer - Data-Centric Driving

General Motors Company; Seattle (WA); On-site; USD 150,000 - 230,000; Full time

Job summary

General Motors is seeking a Staff AI/ML Engineer in the Embodied AI Data Foundations group to develop data-centric AI solutions for autonomous driving. You will design data curation and model-training recipes across real and synthetic data to improve safety and performance on diverse real-world scenarios.

You will collaborate with ML engineers and researchers, run large-scale experiments, and publish insights while applying self-supervised learning, imitation, RL, and fine-tuning to driving

Qualifications

• Master's or PhD in Computer Science, Robotics, Machine Learning.
• Strong ML fundamentals: design clean experiments, pick baselines, read ablations, tell signal from noise.
• Proficiency in Python and PyTorch, with experience training models on large datasets.
• Hands-on experience with data-centric ML: curation, sampling, labeling, or evaluation of large training sets.
• Working knowledge of large-scale foundation models and how they are pre-trained, fine-tuned, and aligned.
• Solid data analysis skills (NumPy, Pandas; SQL or Spark for large datasets).
• Demonstrated ability to deliver applied ML results under real-world constraints and timelines.
• Clear communication: explain results and limits to engineers and non-experts.

Responsibilities

• Design and run experiments that connect data composition to model behavior: dataset mixtures, sampling strategies, curricula, and scaling-law studies that tell us where to invest next.
• Apply methods such as self-supervised pre-training, imitation learning, reinforcement learning, and foundation-model fine-tuning to driving behavior, trajectory generation, and perception tasks.
• Develop data curation and mining methods - auto-labeling, deduplication, difficulty and uncertainty estimation, long-tail and out-of-distribution scenario discovery - to raise the value of every training example.
• Define offline metrics and evaluations that actually predict on-road behavior, and use them to make model and data decisions from evidence rather than intuition.
• Trace model failures back to their root cause in the data, then close the loop by specifying the data needed to fix them.
• Train models at scale across large multi-GPU/multi-node datasets, partnering with platform teams on the pipelines and tooling this requires.
• Collaborate with cross-functional teams to bring models into onboard driving systems, and document learnings and best practices along the way.
• Follow relevant literature and bring promising advances into our recipes and evaluations.

Skills

ML fundamentals

Python

PyTorch

Data-centric ML

Foundation models

Data analysis (NumPy, Pandas; SQL or-S

Education

Master's or PhD in CS/Robotics/ML

PhD/publications/open-source (preferred)

Tools

SQL

Spark

Job description

General Motors is seeking a Staff AI/ML Engineer in the Embodied AI Data Foundations group to develop data-centric AI solutions for autonomous driving. You will design data curation and model-training recipes across real and synthetic data to improve safety and performance on diverse real-world scenarios.

You will collaborate with ML engineers and researchers, run large-scale experiments, and publish insights while applying self-supervised learning, imitation, RL, and fine-tuning to driving