7+ years of hands-on experience building and deploying machine learning models in a

business environment.

• Expert-level proficiency in Python and its data science libraries (e.g., pandas, NumPy,

scikit-learn, XGBoost, spark).

• Advanced proficiency in SQL for querying large and complex datasets.

• 2+ years of demonstrated, hands-on experience developing and deploying

solutions using Large Language Models (e.g., fine-tuning, RAG, prompt

engineering).

• Proven track record of leading complex, end-to-end data science projects that have

delivered significant business impact.

Preferred Qualifications

• Experience with cloud-based ML platforms / ML ops (e.g., AWS SageMaker, MLflow)

and their generative AI services

• Hands-on experience with vector databases

• Familiarity with frameworks like LangChain or LlamaIndex or Agent