Remote Principal AI Lead for Autonomous Driving Data

General Motors; Washington; On-site; USD 170,000 - 250,000; Full time

Benefits offered by this job

GM vehicle discounts

Health benefits

Tuition assistance

Job summary

General Motors seeks a Principal Technical Lead in the Embodied AI Data Foundations organization to drive end-to-end machine learning solutions using real and synthetic datasets for autonomous driving. You will lead novel data curation algorithms, pre-training, post-training and fine-tuning recipes for training AV models, and design scalable data pipelines with cross-functional teams.

You will mentor ML engineers, contribute to a culture of knowledge sharing, and shape onboard/offboard ML

Qualifications

• Bachelor’s, Master’s or PhD in Computer Science with a focus in Robotics and/or Machine Learning
• Experience with large-scale Foundation Models and alignment methods
• Experience delivering applied research in the wild under tight deadlines
• Proficiency in PyTorch and Python
• Experience building and scaling large model training pipelines
• Strong data processing with Numpy, Pandas, Spark
• Excellent communication across diverse teams
• Experience deploying foundation models into production
• Prior robotics or autonomous driving experience

Responsibilities

• Design and implement technologies aligning models to GM’s mission
• Apply unsupervised pre-training, imitation learning, reinforcement learning and guided selection to improve model performance
• Collaborate to align distillation recipes for onboard driving models
• Stay updated on AI frameworks and libraries
• Lead projects end-to-end and document learnings
• Mentor junior team members and promote knowledge sharing

Skills

Foundation Models

Applied Research

PyTorch

Python

Training Pipelines

Numpy

Pandas

Spark

Communication

Deployment

Autonomous Driving

Robotics

Education

PhD in Computer Science/Robotics

Job description

General Motors seeks a Principal Technical Lead in the Embodied AI Data Foundations organization to drive end-to-end machine learning solutions using real and synthetic datasets for autonomous driving. You will lead novel data curation algorithms, pre-training, post-training and fine-tuning recipes for training AV models, and design scalable data pipelines with cross-functional teams.

You will mentor ML engineers, contribute to a culture of knowledge sharing, and shape onboard/offboard ML