Senior / Staff ML Ops Engineer

📋 Description

• Build and evolve our training infrastructure on Kubernetes with Infrastructure — GPU scheduling
• Shape the developer-facing surface — CLIs, SDKs, job submission, templates, paved paths — designed
• Shorten the inner loop. Time to first training run, edit-to-signal latency, local iteration before
• Evangelize best-in-class tooling and frameworks. Track what the ecosystem is shipping, evaluate
• Strengthen the data and artifact layer. Dataset versioning, sharding, and high-throughput loading
• Turn one-off Python into durable tooling — tested, documented, observable libraries, CLIs, and

🎯 Requirements

• 5+ years of software or infrastructure engineering, including tools or platforms used by other
• Hands-on Kubernetes expertise — GPU scheduling, autoscaling, Helm or equivalent, networking
• Excellent Python, and a track record of designing APIs and CLIs other people enjoy using.
• Practical AWS depth: object storage at scale, IAM, GPU compute, networking, cost management, and
• Distributed training in PyTorch (DDP, FSDP, or similar), plus experiment tracking and model
• Fluency with containers, CI/CD, and modern build systems, including large monorepos.

🎁 Benefits

• Competitive compensation and equity awards.
• Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time
• Unlimited Vacation.
• Flexible hours and Work from Home support.
• Daily drinks, snacks and catered meals (when in office).
• Regularly scheduled team building activities and social events both on-site, off-site &amp