Compute Platform Engineering Lead (Multi-Cloud)

Doist; San Francisco, New York (CA, NY); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Stock options

Health & wellness

Meals provided in office

22 weeks parental leave

Job summary

Reflection is seeking a Compute Platform Lead to lead our Kubernetes-based compute layer across multiple neo-clouds. You will mentor a team of systems engineers, guide architectural decisions for multi-cloud scheduling, and stay hands-on to contribute as an IC when needed.

You will also manage vendor deals and ensure the fleet’s reliability for large-scale training runs. This role emphasizes leadership, scalability, and fault-tolerance planning, with close collaboration with training teams and

Qualifications

• Experience leading systems or infrastructure teams while remaining hands-on.
• Strong systems-level engineering with a focus on multi-cloud scheduling and cluster management.
• Proficiency in orchestration, storage, or GPU hardware; able 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.
• Guide technical and architectural decisions for multi-cloud scheduling and GPU deployments.
• Stay hands-on to contribute as an individual contributor.
• Manage day-to-day execution and prioritize work in a fast-paced environment.
• Collaborate with training teams and manage vendor relationships.

Skills

Team leadership

Hands-on engineering

Systems engineering

Kubernetes

GPU hardware

Multi-cloud

Vendor management

Tools

Kubernetes

VAST

Job description

Reflection is seeking a Compute Platform Lead to lead our Kubernetes-based compute layer across multiple neo-clouds. You will mentor a team of systems engineers, guide architectural decisions for multi-cloud scheduling, and stay hands-on to contribute as an IC when needed.

You will also manage vendor deals and ensure the fleet’s reliability for large-scale training runs. This role emphasizes leadership, scalability, and fault-tolerance planning, with close collaboration with training teams and