Senior MLOps Engineer
Core
Ensuring machine learning models run reliably and add value in production for healthcare AI platforms.
Role type
Senior MLOps Engineer
Builds
Production-ready ML infrastructure and CI/CD pipelines for clinical-grade AI systems
Domain
Healthcare AI / Cloud Infrastructure
Deliverable
production ML models
Required skills
ML lifecycle management, model governance (versioning, drift detection), MLOps tools (MLflow, Kubeflow, DVC), CI/CD systems, infrastructure-as-code (Terraform, Helm), data engineering concepts, Python, cloud platforms (AWS, GCP, Azure), container orchestration (Docker, Kubernetes), distributed systems debugging
Preferred skills
Mentoring technical colleagues, designing scalable/secure/observable systems
Technologies
MLflow, Kubeflow, DVC, GitHub Actions, ArgoCD, Terraform, Helm, Docker, Kubernetes, AWS, GCP, Azure
Responsibilities
Own and manage the full lifecycle of ML models and core infrastructure; Build and maintain robust CI/CD pipelines for software and ML workflows; Ensure reliability, scalability, observability, and security of production systems; Automate deployment, orchestration, and environment management; Collaborate with software engineers and product teams to bring ML features to production; Proactively detect and resolve infrastructure and model performance issues
Seniority
Senior, hands-on IC
