It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. 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, environment 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 resource usage, runtime configurations, and code execution patterns for ML workloads. • Collaborate with Data Scientists to translate experimental notebooks into production-ready pipelines. • Implement platform-level controls for environment consistency, dependency management, access control, and model versioning. • Support troubleshooting, debugging, and performance improvements for ML workloads. • Document standards, templates, guidelines, and best practices for MLOps teams. • Work cross-functionally with product, engineering, and analytics teams across PI. Required Qualifications • Bachelor’s/Master’s degree in Computer Science, Engineering, or related field • 6–9 years of relevant experience in ML Engineering, MLOps, or platform engineering • Strong hands-on experience with Databricks, Spark (batch/streaming), Python, Scala • Experience enabling ML lifecycle tools such as MLflow (tracking, packaging, model registration) • Strong CI/CD experience using Git, GitHub Actions, Jenkins, or Azure DevOps • Experience deploying AI/ML models into cloud environments (Azure preferred) • Ability to create and integrate embedding models, semantic vectors, and LLM-driven components • Experience with LangChain for agentic workflows and integration of tools/functions • Strong problem-solving, debugging, and collaboration skills Preferred Qualifications • Experience with Azure OpenAI or OpenAI-compatible LLM APIs • Familiarity with healthcare claims workflows, PI, FWA, provider billing, or pricing • Experience in Agile/Scrum environments • Strong understanding of software engineering best practices, packaging, dependency management Good-to-Have Data Knowledge • Call Center datasets (member & provider interactions) • Provider RCM datasets (billing, coding, authorizations) • EHR/clinical datasets for cross-domain validation If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!