Description
You will design, build, and deploy intelligent, scalable GenAI solutions integrated into enterprise data and analytics platforms.
Responsibilities
- Design and implement end-to-end Generative AI solutions on Databricks, leveraging Unity Catalog, MLflow, Delta Lake, and Vector Search.
- Architect LLM-based multi-agent frameworks for intelligent automation, chatbot systems, and document reasoning tasks.
- Fine-tune and evaluate LLMs and domain-specific NLP models for tasks like NER, Risk Assessment, and Question Answering.
- Build and maintain feature stores and embeddings stores using Databricks or Snowflake.
- Develop reusable ML pipelines using Databricks Repos, MLflow, and Feature Store, automating deployment and retraining.
Required Skills
- 8+ years of professional experience in AI/ML engineering.
- Strong background in Machine Learning, NLP, and LLMs (Transformers, RAG, embedding models).
- Proven experience fine-tuning models using Hugging Face, LangChain, LlamaIndex, or OpenAI API.
- Expertise in Databricks, including Delta Lake, MLflow, Unity Catalog, and Vector Search.
- Proficiency in Python, SQL, PySpark, and Databricks Notebooks.
- Familiarity with Azure Databricks and Azure OpenAI integration.
- Experience building modular codebases and deploying APIs using FastAPI or REST.
- Hands-on experience with MLflow tracking, model registry, and experiment management.
- Bachelor's degree required.