Senior Machine Learning Engineer – Perception & Embodied AI

General Motors; Mountain View (CA); Remote; USD 171,000 - 261,000; Full time

Benefits offered by this job

Health benefits

Retirement savings plan

GM vehicle discounts

Job summary

General Motors seeks a Senior Machine Learning Engineer for Perception in Embodied AI. You will own the end-to-end pipeline for safety-critical ML perception models, from data curation to deployment on the vehicle’s compute platform.

You will lead 3D object detection, multi-modal sensor fusion, and real-time map detection while collaborating with Safety and Systems teams to integrate outputs into vehicle functions.

Qualifications

• BS, MS or PhD in CS, ML, Robotics, or a related quantitative field.
• 5+ years of professional experience with Computer Vision, Deep Learning, and Perception in production.
• Hands-on with PyTorch or TensorFlow for training, experimentation, and debugging.
• Experience fusing data from Camera, LiDAR, and/or Radar.
• Deploying ML models for resource-constrained, real-time embedded systems.
• Ability to drive model improvements through large-scale data analysis.

Responsibilities

• Own the end-to-end ML perception model lifecycle from research to deployment.
• Develop 3D object detection and tracking for vehicles, pedestrians, cyclists.
• Perform real-time map detection of drivable world and road signs.
• Fuse multimodal sensor data (Camera, LiDAR, Radar).
• Scale ML training infra with data mining, loading, and multi-stage evals.
• Optimize models for strict real-time, low-latency on vehicle compute.
• Debug and diagnose performance issues in adversarial scenarios.
• Define robust model-level metrics and collaborate with Safety/Systems.

Skills

Computer Vision

Deep Learning

Sensor Fusion

Embedded Systems

Data Analysis

PyTorch

TensorFlow

Model Deployment

Education

BS/MS/PhD in CS/ML/Robotics

Tools

CUDA

Job description

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 peopleas we aim to makedriving 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 identify, debug, and resolve performance degradations and failures, specifically targeting long-tail and adversarial scenarios (e.g., adverse weather, sensor noise, occlusions).

• Metric Definition: Define and implement robust model-level metrics to aid model development.

• System Integration: Work closely with the Safety, Systems, and other engineering functions to integrate Perception outputs.

Skills & Experience

• BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field.

• 5+ years of professional experience with a focus on Computer Vision, Deep Learning, and Perception in a production environment.

• Deep hands-on experience with modern deep learning frameworks (e.g., PyTorch or TensorFlow) for training, experimentation, and debugging complex DNNs.

• Proven experience working with and fusing data from multiple sensor modalities (Camera, LiDAR, and/or Radar).

• Practical experience deploying and optimizing ML models for resource-constrained, real-time embedded systems.

• Demonstrated ability to drive model improvements through large-scale data analysis, error logging, and data curation.

Bonus:

• Expertise with Transformer-based models for 3D detection, tracking, and scene understanding.

• Technical leadership experience, including mentoring junior engineers and leading major feature development from concept to launch.

• Contributions to relevant academic publications (CVPR, ECCV, ICCV, IROS, NeurIPS etc.).

Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren,Milford or Mountain View, you are expected to report to that location three times perweek, at minimum.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.

• The salary range for this role is $170,600.00 to $261,300.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits:

• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

This job may be eligible forrelocationbenefits.

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