Remote Member of Technical Staff (Software Engineer, GPU Cluster Infrastructure)

Description:

• Build a self-serve compute platform for training and inference workloads.
• Operate and manage a large GPU fleet across multiple cloud providers.
• Develop scheduling and placement logic to optimize GPU resource usage.
• Support both long-running training jobs and production inference services.
• Manage Kubernetes for GPU orchestration across various clusters.
• Implement fault tolerance, autoscaling, and observability for the GPU fleet.
• Collaborate with teams to establish a coherent platform architecture.

Requirements:

• Deep experience with Kubernetes, including custom operators and multi-cluster federation.
• Proven experience managing GPU clusters at scale, including NVIDIA hardware and CUDA.
• Familiarity with orchestrating compute across multiple cloud environments.
• Strong understanding of distributed systems, scheduling, and resource allocation.
• Proficient in infrastructure and systems-level programming (Go, Rust, or C++).
• Experience supporting both training jobs and high-availability inference services.
• Ability to take ownership of problems and navigate ambiguity.

Benefits:

• Opportunity to work with cutting-edge GPU technology and cloud infrastructure.
• Collaborate with a team of experts in AI and machine learning.
• Contribute to the development of a unified platform for AI workloads.