Python ML Engineer

Educational Requirements

• Bachelor of Engineering,BTech,BCA,BSc,MCA,MSc,MTech

Service Line

• Data Analytics Unit

Responsibilities

• Design and develop Generative AI solutions using LLMs (OpenAI, Azure OpenAI, Hugging Face)
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines
• Implement frameworks like LangChain, LangGraph, or LlamaIndex
• Develop and maintain ML models using Python ecosystem
• Work extensively on Azure Databricks for data processing (PySpark)
• Work extensively on Azure Databricks for model training experimentation (MLflow)
• Work extensively on Azure Databricks for Deployment monitoring
• Build scalable data pipelines on Databricks Lakehouse (Delta Lake)
• Integrate vector databases / search systems (Azure AI Search, Pinecone, FAISS, etc.)
• Deploy ML/GenAI solutions using MLOps best practices
• Collaborate with cross-functional teams for production-grade AI solutions

Additional Responsibilities

• Experience with Databricks MosaicML / Vector Search
• Knowledge of Docker, Kubernetes
• Familiarity with CI/CD pipelines
• Experience in building end-to-end AI applications

Technical and Professional Requirements

• Strong programming skills in Python
• Hands-on experience with Generative AI / LLMs, RAG, embeddings, vector search
• LangChain / LangGraph / LlamaIndex
• Mandatory experience in Azure Databricks, PySpark / Spark
• Experience with Azure OpenAI / Azure AI Studio
• MLflow, model serving, MLOps
• Understanding of Transformers, NLP, prompt engineering
• Exposure to REST APIs, FastAPI/Flask (for deployment)

Preferred Skills

• Python
• Machine Learning