Compute Platform Lead — Multi-Cloud & GPU Scale

Reflection AI Ltd; San Francisco (CA); On-site; USD 240,000 - 360,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health & wellness

Job summary

Reflection's Compute Platform team leads a Kubernetes-based, multi-cloud compute layer across neo-clouds. As Compute Platform Lead you will mentor a team of systems engineers, guide architectural decisions, and work with training teams on fault tolerance and remediation.

You will stay hands-on to contribute and ensure the compute fleet supports large-scale training runs. This role also manages vendor relationships, drives capacity planning, and prepares the fleet for next-gen GPUs and

Qualifications

• Experience building, mentoring, and growing systems or infrastructure teams while staying technically hands-on.
• Deep systems-level engineering with a focus on cluster-wide behavior and maintenance.
• Strong coding ability and credibility to earn technical trust of a team.
• Depth in orchestration, storage, or GPU hardware with ability to learn the rest.

Responsibilities

• Build, mentor, and grow a high-performing team of systems engineers.
• Provide front-line leadership to keep the compute fleet reliable and highly available.
• Stay hands-on to contribute as an individual in the team's stack.
• Manage day-to-day execution and project priorities in a fast-paced environment.
• Guide architectural decisions emphasizing scalability, robustness, and reliability.

Skills

Team leadership

Kubernetes

Multi-cloud

GPU deployment

Systems engineering

Vendor management

Architectural decisions

Coding ability

Tools

NCCL

CUDA

Prometheus

Job description

Reflection's Compute Platform team leads a Kubernetes-based, multi-cloud compute layer across neo-clouds. As Compute Platform Lead you will mentor a team of systems engineers, guide architectural decisions, and work with training teams on fault tolerance and remediation.

You will stay hands-on to contribute and ensure the compute fleet supports large-scale training runs. This role also manages vendor relationships, drives capacity planning, and prepares the fleet for next-gen GPUs and