Full-time
Staff ML Infrastructure Engineer (Compute)
Posted by General Motors • United States, AUSTIN TECHNICAL CENTER - AUSTIN TECHNICAL CENTER, United States
About the Role
**Job Description**
**About the Team:**
The **AI Validation Platform** team owns the cloud-agnostic, reliable, and cost-efficient platform that powers GM’s AV efforts. We’re proud to serve as the infrastructure platform for teams developing autonomous vehicles (L3/L4/L5). Our platform supports the simulated validation of state-of-the-art (SOTA) machine learning models, with a focus on performance, availability, concurrency, and scalability. We enable rapid innovation and development by prioritizing high-impact, ML-centric use cases.
**About the Role:**
We are seeking a Staff ML Infrastructure engineer to help build and scale robust Compute platforms for Simulation, data labeling, and data generation workflows. In this role, you will focus on scaling, driving efficiency, and high utilization of cutting-edge GPUs, while also leveling up the platform’s reliability. The successful candidate will have experience building and running scalable distributed...
**About the Team:**
The **AI Validation Platform** team owns the cloud-agnostic, reliable, and cost-efficient platform that powers GM’s AV efforts. We’re proud to serve as the infrastructure platform for teams developing autonomous vehicles (L3/L4/L5). Our platform supports the simulated validation of state-of-the-art (SOTA) machine learning models, with a focus on performance, availability, concurrency, and scalability. We enable rapid innovation and development by prioritizing high-impact, ML-centric use cases.
**About the Role:**
We are seeking a Staff ML Infrastructure engineer to help build and scale robust Compute platforms for Simulation, data labeling, and data generation workflows. In this role, you will focus on scaling, driving efficiency, and high utilization of cutting-edge GPUs, while also leveling up the platform’s reliability. The successful candidate will have experience building and running scalable distributed...
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