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Senior AI Engineer, Databricks, ML, Spark ML

EPAM SystemsUnited States🇺🇸United StatesPosted 12 Sept 2026

Why This Role Stands Out

This Senior AI Engineer role offers a dynamic opportunity to architect and deploy cutting-edge ML and GenAI solutions on Databricks, driving innovation in asset management and industrial diagnostics. You'll thrive here if you possess strong experience with Databricks, Spark ML, and predictive modeling, and are eager to build impactful AI agents and RAG pipelines within a collaborative, hybrid work environment. Apply now to leverage your expertise and grow your career with EPAM Systems!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
15 hours ago
Databricks

Job Description

We are looking for a Senior AI Engineer to build, test, and deploy ML and GenAI components for asset onboarding, industrial diagnostics, and device analytics on Databricks. This specialist will create predictive models, anomaly-detection algorithms, RAG pipelines, document extraction, and AI agent capabilities.

Responsibilities Construct, test, and deploy ML and GenAI components on Databricks Create predictive models for asset onboarding and device analytics Architect and implement anomaly-detection algorithms for industrial diagnostics Build RAG pipelines to enable intelligent information retrieval Deliver document extraction workflows for structured and unstructured data Engineer AI agent capabilities to power advanced automation scenarios Partner with cross-functional teams to translate business needs into AI solutions Enhance model performance, scalability, and reliability in production Track deployed models and iterate based on performance metrics and feedback Requirements 3+ years of experience in AI/ML engineering and solution delivery Expertise in AI Solution Engineering, covering model design and deployment Proficiency in Databricks, Spark ML, and distributed data processing Background in creating predictive models and anomaly-detection algorithms Skills in constructing RAG pipelines, document extraction, and AI agents Understanding of GenAI concepts and industrial diagnostics use cases Capability to design end-to-end ML workflows from data ingestion to deployment Proficiency in English at an Upper-Intermediate level (B2) or higher

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