Compute Platform Engineer - Multi-Cloud GPU Systems

Sierra Ventures; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health & wellness

Meals provided

Parental leave

Unlimited vacation

Visa sponsorship

Team off-sites

Job summary

Reflection is seeking a talented Platform Engineer to join the Compute Platform team in San Francisco. You will help keep our multi-cloud, GPU-enabled compute layer healthy, scalable, and highly available, collaborating with training teams to design fault tolerance and remediation strategies.

You will own cluster-wide tooling, monitoring, and deployment pipelines, enabling next-generation GPU deployments and scalable data replication across clouds.

Qualifications

• Systems-level engineering with a focus on cluster-wide behavior and maintenance.
• Strong coding ability and a focus on systems or GPU infrastructure.
• Deep GPU hardware knowledge beyond standard Kubernetes (e.g., NCCL).
• Alignment with a K8s-first architecture.
• Cloud storage expertise across multiple data centers and datasets at scale.

Responsibilities

• Build and maintain tools for automatic remediation, topology-aware scheduling, capacity planning, and hardware debugging.
• Design and iterate on cluster management stack for workloads across multi-GPU fleets.
• Implement comprehensive cluster-wide monitoring focusing on durability and performance benchmarking.
• Prepare infrastructure for next-generation GPU deployments and larger cluster sizes; own multi-cloud storage and data replication.

Skills

GPU infra

Kubernetes

Cluster management

System reliability

Tools

NVIDIA NCCL

K8s tooling

Job description

Reflection is seeking a talented Platform Engineer to join the Compute Platform team in San Francisco. You will help keep our multi-cloud, GPU-enabled compute layer healthy, scalable, and highly available, collaborating with training teams to design fault tolerance and remediation strategies.

You will own cluster-wide tooling, monitoring, and deployment pipelines, enabling next-generation GPU deployments and scalable data replication across clouds.