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Job Description
EL3 – Databricks MLOps Engineer (Contract)

Domain: Claims Payment Integrity | M&R;, C&S;, E&I; Claims (preferred)
Actuarial & Forecasting Analytics Exposure is an Added Advantage
Tech Stack: Databricks, Spark, Python, Scala, Azure, GitHub Actions, Terraform
AI/LLM Capabilities: Embedding Models, LLM Integration, LangChain Agentic Frameworks
Role Summary

The EL3 Databricks MLOps Engineer is a senior hands-on role responsible for enabling end-to-end machine learning lifecycle automation on Databricks. This includes building and maintaining the CI/CD infrastructure, setting configuration, packaging and deploying ML models, supporting reproducible experiments, and ensuring scalable job orchestration for AI/ML workloads, including LLM-based applications.

The role partners closely with Data Scientists, AI/ML Engineers, platform teams, and business stakeholders within Claims Payment Integrity to ensure robust,



reliable, and automated ML delivery.
Key Responsibilities
- Enable and automate the end-to-end ML lifecycle on Databricks (environment setup, model workflow automation, job scheduling, monitoring hooks).
- Build frameworks, templates, and utilities that make ML development and experimentation reproducible and scalable.
- Implement CI/CD pipelines using Git, GitHub Actions, Jenkins, Azure DevOps, or similar tools.
- Package, version, and deploy ML models into Databricks-managed execution environments.
- Set up automated workflows for training, retraining, evaluation, and scheduled job execution.
- Support creation and integration of machine learning models including classification, forecasting, anomaly detection, NLP, and PI models.
- Enable LLM/GenAI-driven solutions by integrating:
- Embedding model generation
- RAG architectures
- Vector databases
- LangChain agentic workflows
- Optimize reso

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