Design and development of scalable, reliable, high-performance ML framework to support model training at scale.
Model training performance analysis and optimization solutions to scale distributed training workflows and maximize resource utilization across heterogeneous hardware environments, and save cost.
Raise the bar on system observability, debuggability, and operational excellence, and user experience.
Collaborate with cross-functional teams to integrate new features and technologies into the platform.

Requirements

Bachelors degree or higher in Computer Science or equivalent major OR equivalent relevant experience
3+ years professional software engineering experience
2+ years specialized experience in AI/ML infrastructure, e.g., enabling distributed training for scaling large ML models
Strong programming skills in Python, with proficiency in frameworks such as, PyTorch (preferred), TensorFlow, or similar
Experience with distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure).
Willingness to travel to Sunnyvale, CA as needed
Comfortable working in highly ambiguous and dynamic environments.

Benefits

GM offers a variety of health and wellbeing benefit programs.
Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningmodel trainingperformance analysisoptimization solutionsdistributed trainingPythonPyTorchTensorFlowdistributed computingGPU computing

Soft Skills

collaborationproblem-solvingadaptabilitycommunicationoperational excellence

Certifications

Bachelor's degree in Computer Science