Senior ML Infrastructure Engineer (Compute)
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Upload Your ResumeAbout This Role
This role involves building and scaling robust Compute platforms for Simulation workflows, focusing on high utilization of cutting-edge GPUs and ensuring the reliability of the platform. The engineer will play a key role in shaping the architecture, roadmap, and user experience of a robust service supporting AI Validation/Simulation needs.
Responsibilities
- Design and implement core platform backend software components
- Collaborate with Simulation engineers, ML engineers and researchers to understand critical workflows, parse them to platform requirements, and deliver incremental value
- Lead technical decision-making on Compute architecture, cloud capacity provisioning, caching, and auto-scaling mechanisms
- Drive the development of monitoring, observability, and metrics to ensure reliability, performance, and resource optimization
- Proactively research and integrate frameworks, hardware accelerators, and distributed computing techniques
- Lead large-scale technical initiatives across GM’s ML infrastructure
- Raise the engineering bar through technical leadership and by establishing best practices
Requirements
- 4+ years of industry experience, with a focus on high performance backend services
- Strong expertise in Go, or other similar coding languages
- Experience working with cloud platforms such as GCP, Azure, or AWS
- Experience in delivering cross-functional initiatives
- Strong communication skills and a proven ability to drive cross-functional initiatives
- Ability to thrive in a dynamic, multi-tasking environment with ever-evolving priorities
Qualifications
- 4+ years of industry experience, with a focus on high performance backend services
Nice to Have
- Hands-on experience with Cloud VM services Google Compute Engine
- Experience with hardware-in-the-loop validation systems
- Experience with high performance computing (HPC)
- Experience working with or designing interfaces and clients for developer workflows
- Familiarity with telemetry, and other feedback loops to inform product improvements
- Familiarity with hardware acceleration (GPUs) and optimizations
Skills
* Required skills
About General Motors
The AI Validation Platform team owns the cloud-agnostic, reliable, and cost-efficient platform that powers GM’s AV efforts, supporting the simulated validation of state-of-the-art (SOTA) machine learning models.