Strong programming skills in Python Hands-on experience with: ✅ Generative AI / LLMs ✅ RAG, embeddings, vector search ✅ Lang
Chain / Lang
Graph / Llama
Index 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, Fast
API/Flask (for deployment)
Design and develop Generative AI solutions using LLMs (OpenAI, Azure OpenAI, Hugging Face) Build and optimize RAG (Retrieval-Augmented Generation) pipelines Implement frameworks like Lang
Chain, Lang
Graph, or Llama
Index Develop and maintain ML models using Python ecosystem Work extensively on Azure Databricks for: Data processing (PySpark) Model training & experimentation (MLflow) Deployment & monitoring Build scalable data pipelines on Databricks Lakehouse (Delta Lake) Integrate vector databases / search systems (Azure AI Search, Pinecone, FAISS, etc.) Deploy ML/Gen
AI solutions using MLOps best practices Collaborate with cross-functional teams for production-grade AI solutions
Experience with Databricks Mosaic
ML / Vector Search Knowledge of Docker, Kubernetes Familiarity with CI/CD pipelines Experience in building end-to-end AI applications

Strong programming skills in Python Hands-on experience with: ✅ Generative AI / LLMs ✅ RAG, embeddings, vector search ✅ Lang
Chain / Lang
Graph / Llama
Index 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, Fast
API/Flask (for deployment)
Design and develop Generative AI solutions using LLMs (OpenAI, Azure OpenAI, Hugging Face) Build and optimize RAG (Retrieval-Augmented Generation) pipelines Implement frameworks like Lang
Chain, Lang
Graph, or Llama
Index Develop and maintain ML models using Python ecosystem Work extensively on Azure Databricks for: Data processing (PySpark) Model training & experimentation (MLflow) Deployment & monitoring Build scalable data pipelines on Databricks Lakehouse (Delta Lake) Integrate vector databases / search systems (Azure AI Search, Pinecone, FAISS, etc.) Deploy ML/Gen
AI solutions using MLOps best practices Collaborate with cross-functional teams for production-grade AI solutions
Experience with Databricks Mosaic
ML / Vector Search Knowledge of Docker, Kubernetes Familiarity with CI/CD pipelines Experience in building end-to-end AI applications

Python ML Engineer

Job Description