Principal Data Scientist - AI & Machine Learning (Databricks)
Core
Design, develop, evaluate, and deploy predictive, prescriptive, and generative AI solutions including RAG systems and intelligent agents for complex client challenges.
Role type
Principal Data Scientist (AI & Machine Learning)
Builds
Production ML models, RAG systems, intelligent agent-based applications, and scalable MLOps pipelines.
Domain
Artificial Intelligence, Machine Learning, Generative AI, MLOps, Cloud Data Engineering
Deliverable
production ML models
Required skills
Machine Learning (Classification, Regression, Clustering, Feature Engineering), Deep Learning, Python, MLOps (CI/CD, model versioning, monitoring), Cloud platforms (Azure, AWS, GCP, Databricks), LLM orchestration (LangChain, LangGraph), Vector Databases, Prompt Engineering, Model Fine-Tuning (LoRA), Distributed data processing (Apache Spark)
Preferred skills
Reinforcement Learning, Optimization techniques, Knowledge Graphs, Agentic AI frameworks (LlamaIndex, CrewAI, AutoGen), MCP (Model Context Protocol)
Technologies
Scikit-Learn, TensorFlow, Keras, PyTorch, MLflow, FastAPI, Streamlit, Pinecone, Weaviate, Chroma, Milvus, Azure AI Search, LangSmith, RAGAS
Responsibilities
Design and implement end-to-end Machine Learning and Generative AI solutions; Build and optimize Retrieval-Augmented Generation (RAG) systems and intelligent agent-based applications; Develop scalable model deployment and monitoring solutions using MLOps best practices; Mentor and coach junior Data Scientists and Machine Learning Engineers; Lead technical discussions, knowledge transfer sessions, and client-facing AI engagements.
Seniority
Principal, hands-on IC with mentorship and client-facing responsibilities
