Lead Machine Learning Engineer
Core
Build robust infrastructure for automated model pipelines, ensuring deployment reliability and governing the full ML lifecycle from experimentation to production.
Role type
Lead Machine Learning Engineer (Infrastructure & MLOps)
Builds
Production-grade ML infrastructure, automated pipelines, and governance frameworks for data science teams.
Domain
Financial Technology (FinTech), Machine Learning Operations (MLOps)
Deliverable
infrastructure
Required skills
Python engineering, MLflow, Unity Catalog, Databricks, CI/CD, Docker, Kubernetes, Airflow, Prefect, Prometheus, Grafana, Datadog, model governance, versioning, auditability
Preferred skills
None stated
Technologies
MLflow, Unity Catalog, Databricks, Docker, Kubernetes, Airflow, Prefect, Prometheus, Grafana, Datadog
Responsibilities
Guide technical direction of ML engineering stack; lead complex cross-departmental projects impacting model performance and stability; act as bridge between Data Science, Data Engineering, and Development; design and build production-grade ML infrastructure; ensure ML solutions are secure, observable, resilient, and scalable; mentor ML Engineers; identify weaknesses in infrastructure and drive improvements; represent team in technical discussions.
Seniority
Senior, hands-on IC with leadership responsibilities
