Senior MLOps Engineer
Core
Design, build, and operate platforms and pipelines enabling machine learning solutions to move reliably from experimentation to production.
Role type
Senior MLOps Engineer
Builds
Scalable, production-ready ML and data solutions
Domain
Commercial sectors / Data and business consultancy
Deliverable
production ML models
Required skills
Python, SQL, PySpark, Bash, TensorFlow, PyTorch, Scikit-learn, MLflow, Terraform, ARM templates, Ansible, Git, Azure DevOps, Jenkins
Preferred skills
Databricks, SageMaker, VertexAI, client-facing delivery, Agile/Scrum
Technologies
Azure Data Lake, Azure SQL Data Warehouse, Synapse Analytics, Databricks, Delta Lake, Blob Storage, MCP
Responsibilities
Own end-to-end lifecycle of ML models (development, training, deployment, monitoring), implement model versioning and experiment tracking, design and optimize data pipelines, develop scalable data architectures, build CI/CD pipelines, automate model training and deployment, automate infrastructure provisioning
Seniority
Senior, hands-on IC