AI/ML Engineer

Role overview

An AI/ML engineering role advancing the intelligence behind a master data management platform built natively on the Databricks Data Intelligence Platform. The work centers on designing and optimizing LLM-driven entity resolution systems that improve match accuracy, explainability, and performance across enterprise data environments spanning customers, products, suppliers, and other core business entities. It is a self-directed position within a fast-paced startup setting, where solving complex AI challenges and shipping production-grade systems are central to the work.

Responsibilities

- Lead the design, development, and optimization of prompt engineering strategies for LLM-based entity matching, with a focus on accuracy, reduced bias, and enhanced interpretability - Drive continuous improvement of Retrieval-Augmented Generation architectures and evaluation frameworks that strengthen how data is matched, understood, and trusted - Improve precision and recall, reduce bias, and ensure scalable, cost-efficient model performance in production - Translate complex business requirements into robust AI/ML solutions and build user-facing tools that provide transparency and control over matching decisions - Monitor model performance, identify drift, and continuously iterate to improve outcomes - Collaborate closely with product managers, data engineers, and data stewards to deliver integrated solutions and communicate findings to both technical and non-technical stakeholders

Requirements

- Solid experience with LLM-based systems, prompt engineering, and RAG architectures - Background in entity resolution, matching, or related data quality and master data problems - Comfort building production-grade AI/ML systems and evaluation frameworks - Ability to translate business requirements into robust technical solutions and user-facing tools - Experience working with product, data engineering, and data stewardship teams - A self-directed working style suited to a fast-paced startup environment

Nice to have

- Experience with MLOps practices and CI/CD for ML pipelines - Familiarity with distributed computing frameworks beyond Databricks - Experience with other MDM platforms or enterprise data quality tools - Familiarity with cloud platforms such as AWS or Azure for AI/ML deployments

Benefits and work setup

- Full-time position based in India, remote - One opening currently available