Senior Ml Engineer - Embodied Ai Scaling Foundations

General Motors

Multiple Locations
Base: $159,300.00 to $230,700.00; bonus/equity: in...
Hybrid
Machine learning solutions development
Unsupervised pre-training, imitation learning, reinforcement learning
Foundation modeling for object detection/tracking/classification
Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity – into billions+ examples – across different sources, delivering the maximum value to the model through every additional example

Job Summary

  • Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity – into billions+ examples – across different sources, delivering the maximum value to the model through every additional example.
  • Develop and deploy machine learning solutions maximally leveraging multiple sources of data including real and synthetic datasets, directly impacting autonomous driving performance.
  • Contribute to the safety, reliability, and scalability of next-generation autonomous vehicles.

Matching Summary

Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity – into billions+ examples – across different sources, delivering the maximum value to the model through every additional example.

Salary

Base: $159,300.00 to $230,700.00; Bonus/Equity: Incentive pay program based on company, job level, and individual performance; Benefits: Medical, dental, vision, retirement savings plan, paid vacation & holidays, tuition assistance, GM vehicle discounts, and more

Skills & Requirements

Must-have

  • Machine learning solutions development
  • Unsupervised pre-training, imitation learning, reinforcement learning
  • Foundation modeling for object detection/tracking/classification
  • Trajectory generation and safe AI
  • PyTorch and Python proficiency
  • Large-scale data processing workflows

Nice-to-have

  • Human-centered design process
  • Collaborative, high-impact team
  • Leveraging advanced AI techniques
  • Contributing to engineering best practices

Key Requirements

  • 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
  • Experience working with model training pipelines or large-scale data processing workflows
  • Strong data processing skills using 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

Work Rights

Not specified

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