Senior ML, MLOps Engineer
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Job Description
Senior ML / MLOps Engineer at CDW developing scalable machine learning solutions on the Databricks platform. Collaborating with teams to ensure reliable, governed ML workflows in a remote setting.
Responsibilities:
- Design, develop, and maintain Databricks notebooks and jobs supporting data transformation, analytics, and machine learning workloads.
- Develop, integrate, and deploy custom machine learning models using tools such as Azure Machine Learning and MLflow.
- Implement data and AI use cases on the Databricks platform, ensuring seamless integration and operational reliability.
- Configure and manage external AI models within Databricks Model Serving, including secure management of API keys.
- Build scalable asynchronous agents using native Python async patterns to support higher‑concurrency workloads.
- Apply CI/CD and DevOps best practices using Azure DevOps to automate deployment and management of data pipelines and ML infrastructure.
- Inspect and interpret data, metadata, and database structures using SQL editors and built‑in visualizations.
- Collaborate closely with data scientists, analysts, and engineers to translate requirements into production‑ready ML solutions.
- Write clean, modular, well‑documented, and testable Python code following established engineering standards.
Requirements:
- 5 years of experience designing, developing, and deploying machine learning solutions on the Databricks platform.
- Proficiency in Python, including writing modular, testable code and leveraging async programming patterns.
- Familiarity with machine learning concepts, tools, and libraries such as TensorFlow, PyTorch, Scikit‑learn, and MLflow.
- Experience configuring and integrating external AI models and working with AI governance and monitoring capabilities.
- Understanding of CI/CD and DevOps practices supporting data and ML workloads.
- Ability to analyze data and metadata using SQL and visualization tools.
- Strong problem‑solving, collaboration, and communication skills.
Benefits:
- Health insurance
- Professional development opportunities
- Remote work options
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