Senior Machine Learning Engineer – ML Training Infrastructure

General Motors

Senior ML Engineer designing distributed training infrastructure for General Motors. Optimizing AI/ML platforms that power intelligent driving technologies across GM vehicles.

Posted 8/4/2026full-timeSunnyvale • California, Washington • 🇺🇸 United StatesSenior💰 $170,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing scalable ML frameworks, optimizing model-training performance, and integrating advanced technologies for intelligent driving applications. Proficient in Python and experienced with AI/ML infrastructure, distributed computing, and cloud environments.

Highest-signal resume keywords

Python ProgrammingAI/ML InfrastructureDistributed TrainingPyTorchTensorFlow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning FrameworksModel Training OptimizationDistributed ComputingGPU ComputingCloud Environments

Soft Skills

CollaborationAdaptability

Tools & Technologies

AWSGCPAzure

Industry Keywords

Operational ExcellenceUser ExperienceIntelligent Driving Technologies

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design and develop scalable, reliable, high-performance ML frameworks for model training at scale
Analyze and optimize model-training performance across distributed training workflows and heterogeneous hardware
Maximize resource utilization and reduce costs
Improve system observability, debuggability, operational excellence, and user experience
Collaborate with machine learning engineers, research scientists, and cross-functional partners
Integrate new features and technologies into the ML platform
Enable advanced AI research and model development for intelligent driving technologies across General Motors vehicles

Requirements

What you’ll need

Bachelor's degree or higher in Computer Science or equivalent major, or equivalent relevant experience
2+ years of professional software engineering experience
2+ years of specialized experience in AI/ML infrastructure, including enabling distributed training for large ML models
Strong Python programming skills
Proficiency in PyTorch, TensorFlow, or similar frameworks
Experience with distributed computing, GPU computing, and cloud environments such as AWS, GCP, or Azure
Willingness to travel to Sunnyvale, California, as needed
Comfortable working in highly ambiguous and dynamic environments
Selected candidates must report to a GM hub three times a week if living within the specified radius
Required travel of less than 25%

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company, job-level, and individual performance
Relocation benefits may be available
Medical benefits
Dental benefits
Vision benefits
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts