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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 (setting 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 settings.
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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