MLOps Engineer 9Core ML + MLOps
Description
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!