Staff ML Validation Applied Scientist

General Motors (GM)

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$218,800–$335,300 / yr
Posted
25 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $203k
This role $277k
$135k most similar roles pay here $357k

This role pays more than 92% of similar roles. Most pay $162,000–$244,000 — the shaded band above. At the midpoint, this role pays about $277k versus about $203k 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 131 open roles on FindRole.

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

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View all roles at General Motors (GM)

At a glance

TL;DR · Staff ML Validation Applied Scientist

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As a Staff ML Validation Applied Scientist on the Software Validation team within the Autonomous Vehicle organization, you will lead applied machine learning research to improve verification and validation of ML components for autonomous driving at scale. Your daily tasks include building AI validation critics and agentic workflows using LLMs and model-based agents to automate scenario review and anomaly detection, prototyping scalable tools from ML research, and driving simulation-based evaluation of deep learning modules in realistic traffic scenarios. You will need strong proficiency in Python and C++, experience with modern ML for robotic systems, hands-on use of AI agents and workflow orchestration, and the ability to design behavioral metrics for complex ML systems. This role requires a background in autonomous vehicles or ADAS and experience with simulation environments and large datasets for ML evaluation.

Skills

Python C++ LLM-based tools AI agents workflow orchestration CI/CD behavioral metrics ML metrics simulation environments large datasets autonomous vehicles ADAS automation AI validation critics smart monitoring verification and validation tools Kubernetes Terraform AWS

What you'll do

  • Lead the development of ML-centric validation strategies for autonomous vehicle components.
  • Build AI validation critics and agentic workflows using LLMs and model-based agents.
  • Transform advanced ML research into scalable tools integrated into CI/CD pipelines.
  • Drive large-scale simulation-based evaluation of deep learning modules in AV.
  • Provide technical leadership across multiple teams to enhance automation-first software.

What we're looking for

  • 8+ years of experience in Computer Science, Machine Learning, Robotics, or related field.
  • Proficiency in Python and C++ with production system development over large datasets.
  • Deep understanding and evaluation experience with modern ML for robotic systems.
  • Hands-on experience using AI agents, LLM-based tools, and workflow orchestration.
  • Ability to design behavioral and ML metrics for validation of complex systems.
  • Background in autonomous vehicles or vehicle development with ADAS expertise.
  • Experience building verification and validation tools for safety-critical ML systems.

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