Senior Data Scientist

Zohorecruit; Hyderabad; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Zohorecruit is seeking an experienced MLOps/GenAI engineer for Hyderabad to design, build, and productionize large-scale ML and agentic systems.

The role requires 4+ years in Data Science, ML, GenAI, and MLOps, with a proven track record of moving models from sandbox to live production. You will implement robust MLflow-based workflows on Databricks, and own end-to-end deployment and monitoring in a fast-paced environment.

Qualifications

• 4+ years of hands-on experience in Data Science, Machine Learning, GenAI, and MLOps.
• Proven experience productionizing models beyond sandbox/prototype phase.

Responsibilities

• Design, build, and productionize large-scale machine learning, generative AI and agentic systems and models.
• Implement robust MLOps workflows using MLflow to ensure model reliability, scalability, and performance tracking.
• Take ownership of full lifecycle of AI products, ensuring models move from experimental stages to live production environments.

Skills

MLOps

GenAI

Data Science

Machine Learning

Model deployment

Tools

MLflow

Databricks

Databricks Spark

Lakebase

Vector Search

Langchain

Langgraph

Job description

The ideal candidate possesses deep technical expertise in MLOps and GenAI.

Work Mode: Work From Office 5 days a week

• End-to-End Development: Design, build, and productionize large-scale machine learning, generative AI and agentic systems and models.
• Operational Excellence: Implement robust MLOps workflows using MLflow to ensure model reliability, scalability, and performance tracking.
• Production Deployment: Take ownership of the full lifecycle of AI products, ensuring models move successfully from experimental stages to live production environments.
• Experience: 4+ years of hands-on experience in Data Science, Machine Learning, GenAI, and MLOps.
• Track Record: Proven experience productionizing models (must have moved models beyond the sandbox/prototype phase).

Technical Stack:

• Required: Expert-level proficiency with MLflow and model deployment and monitoring on Databricks.
• Required: Experience with Databricks Spark, Lakebase, Vector Search.
• Required: Experience with at least one agent development framework like Langchain, Langgraph, DSPy etc.
• Good to have: Hands on experience with Databricks Apps, AI/BI Dashboards, Genie etc.
• Good to have: Databricks Asset Bundle (DAB), Git, experience with large repo management (GitHub, ADO etc.)