Engineering Manager, GPU Infrastructure
On-siteSan Francisco, California, United States
Job Summary
Lead and mentor a team of engineers specializing in GPU infrastructure, fostering a culture of technical excellence and continuous improvement. Define and execute the technical roadmap for GPU cluster deployment, optimization, and scaling while overseeing topology-aware scheduling, hardware fault detection, and performance optimization systems. Partner with AI researchers to translate emerging infrastructure needs into robust solutions and collaborate with cloud providers to validate and deploy new GPU architectures. Establish observability frameworks for GPU utilization and implement infrastructure-as-code practices for cluster provisioning. Manage vendor relationships, negotiate hardware contracts, and drive cost optimization initiatives while ensuring documentation remains comprehensive and accessible.
Required Qualifications
- Experience managing engineering teams with a focus on technical mentorship and growth
- Deep expertise in ML/HPC infrastructure: GPU/TPU clusters, distributed training frameworks (JAX, PyTorch, TensorFlow), and high-performance computing environments
- Proven experience with Kubernetes at scale: deployment, management, and troubleshooting cloud-native clusters for AI workloads in multi-cloud environments
- Knowledge of infrastructure monitoring tools (Prometheus, Grafana)
- Familiarity with Terraform, ArgoCD, or other IaC tools
- Experience with cost optimization and capacity planning for GPU infrastructure
- Track record of collaborating with AI researchers or ML engineers to solve infrastructure challenges
Desired Qualifications
- Strong communication skills to translate complex technical concepts for diverse audiences
- Ability to make data-informed decisions under pressure
- Experience working in remote, distributed teams
- Commitment to fostering an inclusive and collaborative team culture
- Strong problem-solving abilities with a data-driven approach
- Passion for enabling AI research through robust infrastructure
- Collaborative mindset with a focus on cross-team success
- Willingness to learn and adapt in a fast-paced, evolving environment
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