MLOps / ML platform engineer for biopharma

The company builds a SaaS platform for biopharma and scientific teams that relies on AI and scientific models.

• Own the ML platform architecture and define standards and tooling for other teams
• Build and orchestrate ML workflows using Flyte, Airflow, or similar tools
• Manage experiment tracking, model registries, and artifacts
• Ensure reproducibility and lineage as the platform evolves
• Validate and monitor model behaviour in production
• Manage Kubernetes, Docker, and cloud infrastructure for training and inference workloads
• Build CI/CD for ML and data pipelines
• Improve observability, governance, and reliability across the platform
• Work with scientists and engineers to turn recurring needs into platform capabilities

• At least 5 years of experience in MLOps, ML platform, data platform, or platform engineering
• A software engineering mindset and genuine curiosity about the science behind the product
• Hands-on experience building platforms used by other teams
• Strong Python skills and solid production engineering practices
• Practical experience with Kubernetes, Docker, and CI/CD
• Experience with workflow orchestration and experiment tracking
• Good understanding of data pipelines, quality, versioning, and lineage
• Enough ML knowledge to work confidently with model developers
• Ability to make decisions, state assumptions, and explain trade-offs clearly
• Motivation to focus on platform work and grow in this direction long term
• Будет плюсом: Flyte, MLflow, DVC, Kubeflow or similar tools, Terraform or other infrastructure-as-code tools, AWS, Azure or GCP, Spark, Airflow, dbt or streaming, large, complex or scientific datasets, biotech, pharma or other regulated environments, GxP

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