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Staff ML Engineer, ML Compute Platform. The ML Compute Platform is part of the AI Compute Platform organization within Infrastructure Platforms. Our team owns the cloud-agnostic, reliable, and cost-efficient compute backend that powers GM AI. We’re proud to serve as the AI infrastructure platform for teams developing autonomous vehicles (L3/L4/L5), as well as other groups building AI-driven products for GM and its customers. We enable rapid innovation and feature development by optimizing for high-priority, ML-centric use cases. Our platform supports the training and deployment of state-of-the-art (SOTA) machine learning models with a focus on performance, availability, concurrency, and scalability. We’re committed to maximizing GPU utilization across platforms while maintaining reliability and cost efficiency.
Job Responsibility:
Design core platform backend software components
Thrive in a dynamic, multi-tasking environment with ever-evolving priorities
Interface with other teams to incorporate their innovations and vice versa
Analyze and improve efficiency, scalability, and stability of various system resources
Proactively identify, drive and design large initiatives across GM ML ecosystem
Requirements:
7+ years of industry experience
Expertise in either Go, C++, Python or other relevant coding languages
Strong background with kubernetes at scale
Relevant experience building large-scale with distributed systems
Experience leading and driving large scale initiatives
Experience working with Google Cloud Platform, Microsoft Azure, or Amazon Web Services
Nice to have:
Hands-on experience in ML platforms
Experience with GPU/TPU optimizations
Experience with training frameworks like PyTorch, TorchX
Experience with Ray framework
Leadership/active participation in the open source community
Experience infrastructure applications or similar experience