MLOps Engineer 9Core ML + MLOps
Fractal Analytics
Mumbai; Bengaluru Posted Discovered via the company's careers siteMatch locked
Full time6+ years exp
About the role
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
Domain
Claims Payment Integrity | M&R, C&S, E&I Claims (preferred)
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!
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Not included in the source posting: about the role, benefits.
Skills
machine-learningazuredatabricksllmmlopsartificial-intelligenceci-cdgithub-actionslangchaindevopsgitjenkins
Who can apply
The employer didn't state any visa, work authorization, citizenship or clearance requirements in this posting. Confirm with the employer before applying.
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