THE ROLE
We're looking for a Senior MLOps Engineer who can set the standard for how we build, ship, and operate ML and AI systems at scale. You sit at the intersection of ML infrastructure and SRE — you'll own the path from model and pipeline to reliable production service, and you'll bring DevOps rigor to systems that are historically under-engineered.
This is not a ticket-processing role, and it's not a research role. You'll tackle hard problems — model serving reliability, inference cost and latency, reproducible pipelines, agentic workload operations — and have the scope to solve them properly. Seniors here identify problems before they're asked, and raise the ceiling on what the platform can do.
WHAT YOU'LL WORK ON

Build and operate model and inference serving infrastructure — managing latency, throughput, autoscaling, and reliability for real-time and batch inference across multiple tenants.
Own the ML deployment lifecycle — model registry, versioning, pro...