As a Software Engineer for the ML Ops team, you will help own the production runtime for Phare’s ML stack - deploying, serving, and scaling models across inference endpoints and batch/streaming workflows. Every day you will build progressive delivery pipelines with automated rollouts and rollbacks, manage SLOs for latency and availability, and instrument end-to-end observability (metrics, logs, traces, drift, regression). You’ll harden the platform with Terraform, Kubernetes, and CI/CD, ensuring reproducible, auditable ML releases. To thrive in this role you must have a background in operating ML systems at scale, where uptime and feedback loops matter as much as accuracy.
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed