Role overview
A San Francisco-headquartered tech company - a multiple-time unicorn and recognised leader in enterprise AI infrastructure - is hiring a
Lead MLOps Engineer
to drive their production ML systems in Seattle.
You'll be the technical lead for a team of 4 engineers focused on bridging the gap between data science prototypes and scalable, production-grade AI services. This is a hands-on leadership role - you'll set technical direction, guide architecture decisions, and mentor the team while staying deep in the code.
What you'll work on
- Lead the technical direction for converting research prototypes into production microservices
- Architect and maintain ML deployment infrastructure using Kubernetes, with exposure to tools like Ray and other AI orchestration frameworks
- Design and own MLOps CI/CD pipelines, zero-downtime deployments, and model versioning strategies
- Drive performance optimisation, observability, and reliability for high-scale inference workloads
- Mentor and guide a team of 4 engineers without formal management responsibilities
- Partner with data scientists to ensure research outputs are productionised with scalability in mind
Tags & focus areas
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