Senior Machine Learning Engineer – Perception & Embodied AI

Company: General Motors (GM)

Location: Mountain View, CA (Remote)

Salary: $170,600 - $261,300 a year

Type: Full-time

Remote: Yes

Posted: 2026-03-20

About this role

Job 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.

Role

As a Senior Machine Learning Engineer for Perception within the Embodied AI organization , you will own the end-to-end pipeline for safety-critical ML perception models , from initial research and large-scale data curation to optimization and real-time deployment on the vehicle's compute platform. Your primary mission is to enable the vehicle to accurately and reliably see, classify, and track everything in its environment—from rare road markings and complex intersections to vulnerable road users (VRUs) .

Responsibilities

  • End-to-End Model Lifecycle: Own the design, training, validation, and deployment of deep learning models for core perception tasks such as:
  • 3D Object Detection and Tracking (vehicles, pedestrians, cyclists).
  • Real-time map detection of the drivable world (lanes, road boundaries, traffic signs).
  • Multi-Modal Sensor Fusion (Camera, LiDAR, Radar).
  • Production Pipeline: Build and scale the ML training infrastructure, including data mining and loading, multi-stage training and evaluation, to streamline model development.
  • Performance Optimization: Improve model performance through data iterations, parameter tunings, training strategy and architecture updates to produce reliable models that meet and the strict real-time, low-latency requirements on the vehicle's embedded hardware.
  • Model Debugging: Conduct rigorous, data-driven analysis to ide...

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