Sr. Data Engineer with ML

Responsibilities

• Design, implement, and maintain a hybrid ML infrastructure that connects on-premises open-source tools with cloud platforms like Databricks.
• Enable experiment tracking, model versioning, and lifecycle management using MLflow integrated with Databricks notebooks.
• Manage the registration, versioning, and deployment of machine learning models across environments.
• Collaborate with data scientists and ML engineers to streamline workflows and ensure scalable, reliable model deployment.
• Configure MLflow servers and APIs to connect securely and efficiently with existing data sources and deployment targets.
• Optimize data pipelines and model deployment processes for both on-premises and cloud environments.
• Ensure best practices for reproducibility, security, and scalability in ML workflows.

Qualifications

• Proven experience with MLflow, Databricks, and open-source machine learning frameworks.
• Strong understanding of data engineering, model lifecycle management, and cloud computing.
• Experience with deploying and managing machine learning models in hybrid environments.
• Knowledge of Apache Spark, Python, and Linux/Unix systems.
• Excellent collaboration and communication skills.

Pay

TBD

Schedule

W2 contract, long term duration