Senior MLOps Engineer I

Role Overview

As a Senior MLOps Engineer (I) at Zeitview, you will help productionize models (and LLM/agent-backed workflows) built by ML Scientists, Data Scientists, and Perception Engineers. You’ll build and maintain the infrastructure, pipelines, tooling, monitoring, and release processes that move models from research notebooks to reliable, monitored deployments across multiple industry verticals.

Responsibilities

• Partner with Scientists to translate research code into dependable, scalable production services without slowing research velocity.
• Cross-functional collaboration with DevOps and Software Engineering on infrastructure requests and shared data pipeline needs.
• Model registry, deployment & release management
  • Maintain and improve the model registry and deployment pipelines.
  • Help implement safer release practices such as shadow deployments and rollback procedures.
• Cloud infrastructure & CI/CD
  • Build, maintain, and debug cloud infrastructure and CI/CD pipelines for ML workloads.
  • Work with Engineering/DevOps on infrastructure-as-code and compute cost optimization.
• Monitoring, drift & reproducibility
  • Implement monitoring/observability for models and pipelines.
  • Support experiment tracking and dataset/model versioning; track performance and drift over time.
• Ongoing maintenance & platform support
  • Keep deployed systems healthy (upgrades, capacity/cost management, data pipeline upkeep, retraining/redeployment support).
• Standards & documentation
  • Define/document conventions for model versioning, promotion (staging → production), and model lineage/documentation.
  • Build tooling to enable scientist/engineer self-serve workflows.
• Communication: ensure R&D goals and constraints are clearly understood by Software Engineering and DevOps teams.

Requirements

• The posting excerpt ends after “Qualifications…”, so specific required qualifications are not provided in the text.