Data Scientist / MLOps Engineer

Role Overview

We are seeking a highly motivated and technically strong Data Scientist / MLOps Engineer to join our growing AI & ML team. This role involves the design, development, and deployment of scalable machine learning solutions, with a strong focus on operational excellence, data engineering, and GenAI integration.

Responsibilities

• Build and maintain scalable machine learning pipelines using Python.
• Deploy and monitor models using MLFlow and MLOps stacks.
• Design and implement data workflows using standard python libraries such as PySpark.
• Leverage standard data science libraries (scikit-learn, pandas, numpy, matplotlib, etc.) for model development and evaluation.
• Work with GenAI technologies, including Azure OpenAI and other open source models, for innovative ML applications.
• Collaborate closely with cross-functional teams to meet business objectives.
• Handle multiple ML projects simultaneously with robust branching expertise.

Requirements

• Expertise in Python for data science and backend development.
• Solid experience with PostgreSQL and MSSQL databases.
• Hands-on experience with standard data science packages such as Scikit-Learn, Pandas, Numpy, Matplotlib.
• Experience working with Databricks, MLFlow, and Azure.
• Strong understanding of MLOps frameworks and deployment automation.
• Prior exposure to FastAPI and GenAI tools like Langchain or Azure OpenAI is a big plus.
• B.Tech in Computer Science, Data Science, Mechanical Engineering, or a related field.

Skills

• Python
• PostgreSQL
• MLFlow
• Azure
• Scikit-Learn

Benefits

• Leave encashment
• Paid sick time
• Paid time off
• Provident Fund
• Work from home