Senior ML Validation Engineer

General Motors (GM)

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$144,700–$261,300 / yr
Posted
96 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $217k
This role $203k
$131k most similar roles pay here $275k

This role pays less than 57% of similar roles. Most pay $183,343–$249,750 — the shaded band above. At the midpoint, this role pays about $203k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

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 126 open roles on FindRole.

Listed pay typically runs $170,000–$258,500 across 75 roles with salary data.

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At a glance

TL;DR · Senior ML Validation Engineer

The Senior ML Validation Research Engineer will join a dynamic team focused on advancing machine learning validation for robotics and autonomous driving systems. This role involves transforming cutting-edge research into practical tools that enhance the efficiency, accuracy, and coverage of ML system validation through simulation-based evaluation. Daily tasks include developing scenario generation tooling, creating robust metrics for uncertainty detection, and integrating prototypes into CI/CD pipelines. The ideal candidate has expertise in Python, PyTorch, JAX, or TensorFlow, along with a background in machine learning research and experience in simulation-driven ML evaluation. Key areas of focus are scenario synthesis, coverage-based testing, and OOD detection, requiring strong collaboration skills across Simulation, Safety, Systems Engineering, and other cross-functional teams.

What you'll do

  • Develop robust metrics and uncertainty detection methods for autonomy ML systems.
  • Advance ML research for open and closed loop simulation validation.
  • Create scenario generation tooling for coverage-guided testing and rare-event discovery.
  • Evaluate deep learning modules in perception, prediction, and planning using realistic simulations.
  • Integrate prototype tools into CI/CD pipelines for efficient ML system validation.

What we're looking for

  • MS + 5 years or PhD + 3 years in ML, Robotics, Computer Science, or related field.
  • Experience with simulation-driven evaluation of robotics/autonomy systems.
  • Strong proficiency in Python and deep learning frameworks (PyTorch, JAX, TensorFlow).
  • Ability to translate complex ML research into functional prototypes.
  • Experience integrating ML evaluation tools into CI/CD pipelines.
  • Proven research impact through publications, internal tools, or patents.
  • Strong communication skills for cross-functional collaboration.

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