Senior Machine Learning Engineer – ML Training Infrastructure

Jobtailor

California (MO)

On-site

USD 140,000 - 190,000

Full time

14 days+

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Job summary

General Motors in the United States seeks an experienced ML platform engineer to design scalable ML frameworks for large-scale model training. You will optimize distributed training performance, improve observability, and collaborate with ML engineers, researchers, and cross-functional partners.

You'll work with PyTorch and TensorFlow, leverage AWS/GCP/Azure, and travel to Sunnyvale as needed, reporting to a GM hub thrice weekly if within radius.

Qualifications

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

Responsibilities

Design and develop scalable, reliable ML frameworks for model training at scale.
Analyze and optimize model-training performance across distributed workflows.
Maximize resource utilization and reduce costs.
Improve system observability, debuggability, and user experience.
Collaborate with ML engineers, researchers, and cross-functional teams.
Integrate new features and technologies into the ML platform.
Enable AI research and model development for intelligent driving tech across GM vehicles.

Skills

Python Programming

AI/ML Infrastructure

Distributed Training

PyTorch

TensorFlow

Collaboration

Adaptability

Distributed Computing

Cloud Environments

Education

Bachelor's degree in Computer Science

Tools

AWS

GCP

Azure

Job description

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

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%

Core Competencies

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.

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