Data Scientist

Architect agentic AI workflows and complex stateful applications using frameworks like LangGraph.

Build, evaluate, and scale LLM-powered application chains and orchestration workflows utilizing LangChain.

Track, log, and govern machine learning experiment lifecycles, parameters, and model deployments via MLflow.

Package data models and AI applications into lightweight, isolated containers using Docker for seamless deployment.

Manage codebase versioning, team repositories, and collaborative feature branches securely using Git.

Execute core Data Scientist functions, including exploratory data analysis, feature engineering, and model tuning.

Monitor deployed machine learning models in production to prevent data drift and ensure runtime reliability.

Minimum Qualifications: Bachelors / Masters in a quantitative field (CS, Data Science, Mathematics, or equivalent).

0–1 Yrs of experience, making it an excellent opportunity for freshers or junior data scientists with strong modern AI skills.

Hands-on experience or project exposure with LLM orchestration tools like LangGraph, LangChain, and MLOps platforms like MLflow.

Verifiable command over version control via Git and containerization concepts using Docker.

Exceptional logical reasoning skills paired with a fast learning curve for emerging Generative AI frameworks.