AI/ML Engineer

Lakefusion; United States; Remote; USD 150,000 - 220,000; Full time

Benefits offered by this job

Remote work in India

Job summary

Lakefusion is seeking an AI/ML engineer to advance a master data management platform built on Databricks. You will design and optimize LLM-driven entity resolution, focusing on match accuracy, explainability, and scalable performance across enterprise data domains.

In a fast-paced startup, you will own prompt engineering strategies, refine RAG architectures, monitor drift, and ship production-grade AI/ML solutions with clean, user-facing tooling and transparent decision processes for technical

Qualifications

• 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.

Responsibilities

• Lead the design, development, and optimization of prompt engineering strategies for LLM-based entity matching.
• Drive continuous improvement of Retrieval-Augmented Generation architectures and evaluation frameworks.
• 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.
• Monitor model performance, identify drift, and continuously iterate to improve outcomes.
• Collaborate with product managers, data engineers, and data stewards to deliver integrated solutions and communicate findings to stakeholders.

Skills

LLM-based systems

Prompt engineering

RAG architectures

Entity resolution

Production-grade ML

Tools

Databricks platform

CI/CD for ML pipelines

Job description

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