Senior AI/ML Engineer, Future Sensing, Embodied AI

General Motors (GM)

Confirmed live yesterday Trusted
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$182,400–$250,600 / yr
Posted
100 days ago
Freshness
Confirmed live yesterday

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Competitive pay

How this pay compares to similar roles

Similar $211k
This role $216k
$156k most similar roles pay here $274k

This role pays more than 52% of similar roles. Most pay $167,537–$254,750 — the shaded band above. At the midpoint, this role pays about $216k versus about $211k for comparable roles.

Based on 240 similar postings.

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About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 116 open roles on FindRole.

Listed pay typically runs $160,200–$245,000 across 59 roles with salary data.

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At a glance

TL;DR · Senior AI/ML Engineer, Future Sensing, Embodied AI

Senior AI/ML Engineer - Future Sensing, Embodied AI joins the Embodied AI team to develop and evaluate machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios. This role involves building perception models for object detection, tracking, classification, and multi-modal sensor fusion using cameras, lidar, and radar. The engineer will apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling, and foundation modeling to solve complex problems in the autonomous driving domain. Key responsibilities include training, fine-tuning, and validating models while managing production pipelines for data loading and error analysis. Required skills include proficiency in Python and PyTorch, along with experience using NumPy, Pandas, and Apache Spark. The role focuses on solving technical challenges related to sensing tradeoffs across varied environmental conditions like weather, lighting, and occlusion.

What you'll do

  • Develop and improve AI/ML solutions for autonomous driving and future sensing objectives.
  • Apply advanced techniques like imitation learning, reinforcement learning, and foundation modeling to solve perception problems.
  • Evaluate perception models using camera, lidar, radar, and multi-modal sensor fusion data.
  • Perform model training, fine-tuning, validation, debugging, and performance optimization for sensor-fusion tasks.
  • Define and implement robust metrics for detection, localization, and model robustness under varied environmental conditions.
  • Analyze sensing tradeoffs across different weather, lighting, and noise scenarios using real and synthetic data.
  • Manage production pipelines including data loading, error analysis, and deployment-oriented support.
  • Integrate models and algorithms into onboard driving systems and future sensing evaluation workflows.

What we're looking for

  • Bachelor’s or Master’s degree in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field.
  • Experience applying machine learning techniques to real-world systems or large-scale datasets.
  • Experience building AI/ML or perception systems in autonomy, robotics, computer vision, or related domains.
  • Proficiency in PyTorch and Python.
  • Experience working with model training pipelines or large-scale data processing workflows.
  • Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark.
  • Experience with model validation, debugging, and failure analysis in ML or perception settings.
  • Experience with one or more perception domains including object detection, segmentation, tracking, reconstruction, localization, or sensor fusion.

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