MLOps Engineer 9Core ML + MLOps
Fractal Analytics3 months ago
Pune, India +4 moreSenior
Responsibilities
- Automate the end-to-end machine learning lifecycle on Databricks, including environment setup, model workflows, scheduling, and monitoring hooks.
- Build reusable frameworks, templates, and utilities for reproducible and scalable ML development and experimentation.
- 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.
- Automate training, retraining, evaluation, and scheduled job execution workflows.
- Support machine learning models for classification, forecasting, anomaly detection, NLP, and payment integrity use cases.
- Integrate embedding models, RAG architectures, vector databases, and LangChain agentic workflows for LLM and GenAI solutions.
- Optimize resource usage, runtime configurations, and code execution patterns for ML workloads.
- Convert experimental notebooks into production-ready pipelines in collaboration with Data Scientists.
- Implement controls for environment consistency, dependency management, access control, and model versioning.
- Troubleshoot, debug, and improve ML workload performance.
- Document MLOps standards, templates, guidelines, and best practices.
- Collaborate with product, engineering, analytics, platform, and business stakeholder teams.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 6–9 years of relevant experience in ML Engineering, MLOps, or platform engineering.
- Strong hands-on experience with Databricks, Spark batch and streaming, Python, and Scala.
- Experience with MLflow for experiment tracking, packaging, and model registration.
- Strong CI/CD experience with Git, GitHub Actions, Jenkins, or Azure DevOps.
- Experience deploying AI/ML models into cloud environments, preferably Azure.
- Ability to create and integrate embedding models, semantic vectors, and LLM-driven components.
- Experience with LangChain agentic workflows and tool or function integration.
- Strong problem-solving, debugging, software engineering, packaging, dependency management, and collaboration skills.
- Preferred experience with Azure OpenAI or OpenAI-compatible LLM APIs.
- Healthcare claims, payment integrity, fraud/waste/abuse, provider billing, pricing, call-center, provider RCM, or EHR/clinical data experience is preferred.
- Experience in Agile/Scrum environments is preferred.
Benefits
- Contract position.
- The posting describes a collaborative environment with opportunities to work across product, engineering, analytics, platform, and business teams.
Tech Stack
Categories
About Fractal Analytics
Fractal builds enterprise AI and analytics solutions—delivered as consulting services and software products—for large global enterprises, especially Fortune 500 firms. Its teams embed AI in decisions across marketing, pricing, supply chain, forecasting, and customer experience. Founded in 2000 and headquartered in New York, Fractal is publicly listed and operates across North America, EMEA, and APAC.