FR
Full time
🤖 AI / ML
MLOps Engineer (Databricks — Core ML + MLOps) at Fractal
Listed by DevShelfHub
Mumbai, India
Hybrid
Senior · 6–9 yrs
About the Role
Fractal is hiring an EL3 Databricks MLOps Engineer (Contract) in Mumbai for Claims Payment Integrity—enabling end-to-end machine learning lifecycle automation on Databricks with LLM and agentic framework integration.
This senior hands-on role partners with Data Scientists to deliver robust, automated ML delivery including RAG architectures and LangChain workflows.
What you'll do
- Enable and automate end-to-end ML lifecycle on Databricks
- Build frameworks and utilities for reproducible, scalable ML experimentation
- Implement CI/CD pipelines using Git, GitHub Actions, Jenkins, or Azure DevOps
- Package, version, and deploy ML models into Databricks-managed environments
- Set up automated workflows for training, retraining, evaluation, and scheduling
- Support ML models: classification, forecasting, anomaly detection, NLP, PI models
- Integrate embedding models, RAG architectures, vector databases, LangChain workflows
- Optimize resource usage and runtime configurations for ML workloads
- Translate experimental notebooks into production-ready pipelines
- Implement platform controls for environment consistency, dependency management, access control
- Document standards, templates, and best practices for MLOps teams
What we're looking for
- Bachelor's/Master's in Computer Science, Engineering, or related field
- 6-9 years in ML Engineering, MLOps, or platform engineering
- Strong hands-on Databricks, Spark (batch/streaming), Python, Scala
- ML lifecycle tools: MLflow (tracking, packaging, model registration)
Skills & Technologies
Required
Bachelor's/Master's in Computer Science, Engineering, or related field
6-9 years in ML Engineering, MLOps, or platform engineering
Strong hands-on Databricks, Spark (batch/streaming), Python, Scala
ML lifecycle tools: MLflow (tracking, packaging, model registration)
CI/CD with Git, GitHub Actions, Jenkins, or Azure DevOps
Deploying AI/ML models into cloud environments (Azure preferred)
Embedding models, semantic vectors, and LLM-driven components
LangChain for agentic workflows and tool/function integration
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- Build MLOps infrastructure for healthcare claims analytics with GenAI integration.
- Enable end-to-end ML lifecycle automation on Databricks
- Build CI/CD pipelines with Git, GitHub Actions, Jenkins, Azure DevOps
- Package, version, and deploy ML models in Databricks environments
- Integrate LLM/GenAI: embeddings, RAG, LangChain agentic workflows
- Support classification, forecasting, anomaly detection, NLP, PI models
- Claims Payment Integrity domain with actuarial analytics exposure
- Contract role with cross-functional product and engineering collaboration
- Document standards, templates, and MLOps best practices
- Azure cloud deployment experience
- Healthcare claims workflow domain knowledge opportunity
About Fractal
Fractal is a global AI company powering every human decision in the enterprise. With expertise in artificial intelligence, design, engineering, and digital transformation, Fractal partners with Fortune Global 100 companies to unlock value from data-to-decision journeys.
- Industry
- Technology
- Company Size
- 500+
- Website
- fractal.com
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Job Details
- Type
- Full time
- Level
- Senior
- Experience
- 6–9 years
- Location
- Mumbai, India
- Work Mode
- Hybrid
- Category
- AI / ML
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