Machine Learning Engineer
Core
Building scalable data pipelines and cloud-based data platforms to support enterprise AI solutions for Fortune 1000 clients.
Role type
Senior Machine Learning Engineer (Data Infrastructure & MLOps)
Builds
Production-grade data pipelines, cloud data platforms, and ML model deployment workflows
Domain
Enterprise AI, Cloud Data Platforms, MLOps
Deliverable
production ML models | infrastructure
Required skills
Python, software engineering principles (OOP, functional programming), cloud data platforms (Azure, Databricks), distributed data processing (Spark, Delta tables), containerization (Docker), CI/CD pipelines, automated testing
Preferred skills
MLOps frameworks (MLflow, AzureML, Databricks Model Serving), model lifecycle management, feature stores, vector stores, low-latency inference pipelines
Technologies
Python, Azure, Databricks, Spark, Delta tables, Docker, MLflow, AzureML
Responsibilities
Configure and optimize cloud-based data platforms and cluster settings; build and optimize large-scale data processing pipelines; implement DevOps practices including containerization and CI/CD; translate business requirements into scalable technical solutions; collaborate with cross-functional teams on data and ML solutions
Seniority
Senior, hands-on IC