Machine Learning Ops and Data Engineer
Core
Build and maintain scalable data platforms and production ML infrastructure, ensuring reliable data flows and model deployment for analytics, reporting, and risk use cases.
Role type
Mid-level Machine Learning Ops and Data Engineer
Builds
Cloud-based analytical, reporting, and machine learning infrastructure; production-ready ML models; automated data pipelines
Domain
Financial services / Data Engineering / MLOps
Deliverable
production ML models | infrastructure
Required skills
Python, SQL, ETL pipeline design, CI/CD, Docker, cloud infrastructure (Azure), ML lifecycle management, software debugging, technical documentation
Preferred skills
LLM usage for code generation, scikit-learn, XGBoost
Technologies
Azure, Docker, scikit-learn, XGBoost, CI/CD pipelines
Responsibilities
Deploy and monitor ML models in production; develop automation for model updates and data processing; design and optimize ETL pipelines; troubleshoot performance issues in data warehouses and model deployments; maintain technical documentation for data and model processes
Seniority
Mid-level, hands-on IC