Senior ML Ops Engineer
RemoteBerlin, State of Berlin, Germany or Germany
Job Summary
Build and maintain ML infrastructure end-to-end, extending CI/CD pipelines, model orchestration, and automated training pipelines to scale reliably without manual intervention. Own model deployment and serving by defining standards for low latency and high availability, while establishing feature stores, model registries, and automated monitoring for performance and data drift. Operationalize Kubernetes autoscaling and GPU provisioning as self-service tools, taking models from experimentation to production. Partner with Operations to design resilient monitoring using advanced observability tooling and implement automation to reduce manual interventions. Empower Data Scientists through standardized, optimized workflows that streamline the model development lifecycle. This role requires commuting to the Berlin office three times a week.
Required Qualifications
- Experience building and operating ML platforms in production environments
- Solid working knowledge of containerization and orchestration (Docker, Kubernetes), Linux internals, and model serving at scale
- Familiarity with ML lifecycle tooling, including orchestration frameworks, feature stores, model registries, and drift or performance monitoring
- Experience owning production systems: defining service-level objectives (SLOs), building observability (for example, using tools such as Prometheus, Grafana, or Datadog), participating in incident response, and diagnosing large-scale failures systematically
- Comfort writing production-quality code in Python or a comparable language
- Experience modernizing production infrastructure with attention to reliability, risk, and cost — including thoughtful sequencing of work to maintain availability and continuity for live systems
- The ability to take ownership of technical outcomes, advocate for decisions using data, and communicate clearly in writing and in person — to both technical and non-technical audiences
- This role requires commuting to the Berlin office 3 times a week
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