Staff Artificial Intelligence Machine Learning Engineer

General Motors (GM)

Remote Hybrid

Quick summary

Work type
Remote
Location
Milford, MIAustin, TXMountain View, CA
Posted
5 days ago

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Salary context

How this pay compares to similar roles

Similar $217k
$161k most similar roles pay here $275k

This listing doesn't post a salary. Most similar roles pay $184,412–$249,750.

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 123 open roles on FindRole.

Listed pay typically runs $160,200–$261,300 across 73 roles with salary data.

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At a glance

TL;DR · Staff Artificial Intelligence Machine Learning Engineer

General Motors is hiring a Staff AI/ML Engineer for its Vehicle Mechatronic Embedded Controls (VMEC) Analytics team, where you will design and build end-to-end machine learning solutions for diagnostics, prognostics, and test analytics. You’ll work on production-grade ML pipelines using Azure and Databricks, develop robust services and tools, apply practical methods like tree-based models and deep learning, and ensure model observability in production. The role involves collaborating with SMEs to embed AI/ML into daily workflows, mentoring junior engineers, and setting high standards for testing and deployment. Ideal candidates have a graduate degree and 7+ years of hands-on experience with Python, SQL, PyTorch, TensorFlow, MLflow, and cloud platforms like Azure Databricks. Experience in vehicle data, diagnostics modeling, vector search, and automotive engineering is preferred.

What you'll do

  • Design and build end-to-end AI/ML solutions for diagnostics and prognostics.
  • Implement production-grade ML pipelines on Azure and Databricks for batch and streaming workloads.
  • Develop robust, observable ML services that simplify complex vehicle data usage.
  • Apply practical ML methods focusing on reliability, explainability, and impact.
  • Own model observability in production, including metrics, dashboards, alerts, and remediation workflows.

What we're looking for

  • 7+ years of hands-on experience designing, building, and operating machine learning systems in production.
  • Strong proficiency in Python and SQL for production-quality code in multi-developer environments.
  • Practical experience with ML frameworks like PyTorch, TensorFlow, or scikit-learn and MLOps tooling.
  • Experience building data and ML workloads on cloud platforms such as Microsoft Azure and Databricks.
  • Ability to turn real-world problems into shippable AI/ML solutions from data exploration to deployment.
  • Strong understanding of ML system behavior in production and experience with logs, metrics, and traces.

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