Role overview
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards Resources .
What you'll work on
- Lead the design and development of scalable, reliabile, high-performance ML framework to support model training at scale.
- Lead model training performance analysis and optimizaiton 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.
What we're looking for
- Bachelors or higher degree in Computer Science or equivalent major or equaivalent experience
- 7+ years professional software engineering experience
- 3+ 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 (prefered), 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
What Will Give You a Competitive Edge (preferred qualifications):
- Self-motivated, strong execution, impact-delivering oriented
- Extensive knowledge and experience with PyTorch 2.x+ and distributed training framework
- Experience with design and development of training framework that supports FSDP, Pipeline Parallelism and other scalable solutions to training large foundational models
- Experience with profiling, analysis, debugging and optimizing training and dataloading performance.
- Excellent communication skills to resolve controversial, make consensus, communicate risks and give constructive feedback
Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Machine Learning Mlops