MLOps & Data Engineer

About the role

We are looking for an MLOps & Data Engineer to build the infrastructure that allows our ML team to process clinical documents, run experiments, deploy models, monitor systems, and support annotation/evaluation workflows. You will work closely with Research Engineers, ML Evaluation Engineers, Clinical AI Data Specialists, Engineering DevOps, and backend teams.

What you'll do

• Build and maintain data pipelines for clinical document processing, OCR outputs, text extraction, metadata normalization, and dataset preparation
• Support deployment cycles for ML/LLM systems in collaboration with Engineering DevOps
• Build and maintain training, inference, and evaluation infrastructure
• Improve experiment tracking, model versioning, dataset versioning, CI/CD, monitoring, observability, and reproducibility
• Build internal tools and lightweight Streamlit apps for annotation, clinical review, evaluation, QA, data inspection, and project operations

What you need

• 3–6 yrs of experience
• MLOps
• Machine learning
• Python
• ETL
• LLMs
• CI/CD
• Any graduate

Good to have

• Airflow
• FastAPI
• Kubernetes
• Terraform
• Prototyping
• Docker