Own AI, ML, and GenAI capabilities on Databricks , building production-grade ML and LLM solutions using Databricks native features.
Design ML & GenAI architectures on Databricks
Implement MLOps using MLflow, Feature Store, Model Registry
Build RAG, embeddings, and LLM fine-tuning pipelines
Use Databricks Vector Search and serving endpoints
Create AI accelerators and reusable assets
Support AI-focused Databricks presales and PoCs
8–12 years in ML / AI / Data Science
3–5 years building ML solutions on Databricks
2+ years hands-on with LLM-based solutions
Databricks ML platform & MLflow
Python, Spark ML, distributed training
LLM frameworks (LangChain, HuggingFace)
Feature engineering & model monitoring
Responsible AI & governance basics
Certifications (Preferred)
