Description

ABOUT THE ROLE

We are looking for a Python ML Engineer (LLM Ops) to build, deploy, and operationalize scalable machine learning and Generative AI solutions on cloud platforms. The role focuses on developing production-grade ML pipelines, LLMOps workflows, and NLP solutions using Python, Databricks, AWS, and SQL while supporting healthcare data initiatives.

KEY RESPONSIBILITIES

• Design and develop production-ready ML and LLM applications using Python.
• Build scalable ML pipelines on Databricks and AWS.
• Implement LLMOps for deployment, monitoring, evaluation, and model lifecycle management.
• Develop cluster and job orchestration for large-scale processing.
• Build automated CI/CD pipelines for ML workloads.
• Develop NLP solutions for structured and unstructured healthcare data.
• Optimize scalable compute orchestration to eliminate processing bottlenecks.
• Collaborate with architects, data engineers, and QA teams.

REQUIRED SKILLS & EXPERIENCE

• Python
• Machine Learning Engineering (MLE)
• LLMOps
• Databricks
• AWS
• SQL
• Natural Language Processing (NLP)
• Cluster & Job Orchestration
• Scalable Compute Orchestration
• Automated CI/CD Pipelines
• Git

MUST HAVE

• PHI / HIPAA-compliant data handling practices
• HL7 ADT message format knowledge
• Recent experience in Healthcare data domain

NICE TO HAVE

• MLflow
• Docker/Kubernetes
• FHIR
• RAG
• Vector Databases

Key Skills

Education

Any Graduate