Sr. Data Scientist/ML Engineer

Roles and Responsibilities :

•  Strong fundamentals of data analysis, EDA or data science
• Python, Azure, AI/GenAI engineering
• AI Engineering - Lang Graph, Auto Gen, Vector DB's
• Cloud Systems - Azure - Data Lake, Databricks, AI Search
• Procurement business knowledge or other related business domains like supply chain, manufacturing, breweries or contract intelligence, etc,
• Strong communication and ability to work independently
• Basic foundations of MLOPs (Data drift, Model drift, concept drift, feature store, training pipelines)

Good To Have :

• Design and implement ML pipelines from training to deployment (batch & real-time)
• DevOps - ML Model Deployment using Docker, CI/CD (GitHub Actions, Azure DevOps)
• Prompt engineering and evaluation for GPT-based extraction tasks
• Enterprise domain knowledge: source-to-pay lifecycle, SAP, contract clause structures
• RabbitMQ/Kafka, Airflow, Edge VM deployments, FastAPI/Flask, API deployment, E2E Product building experience