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Senior AI Engineer/ Databricks, Machine Learning

Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting
Employment
Not stated

What you’ll work on

Full posting
  • Design predictive models for asset onboarding and device analytics

  • Architect and build anomaly-detection algorithms for industrial diagnostics

  • Develop RAG pipelines for intelligent information retrieval

  • Build document extraction workflows for structured and unstructured data

  • Track deployed models and refine them using performance data and feedback

From the employer’s posting
Design predictive models supporting asset onboarding and device analytics
Architect and build anomaly-detection algorithms for industrial diagnostics
Develop RAG pipelines that enable intelligent information retrieval
Build document extraction workflows handling both structured and unstructured data
Track deployed models and refine them based on performance data and user feedback

What you’ll bring

All qualifications

Core experience

  • At least 3 years in AI/ML engineering and solution delivery
  • Skilled in Databricks, Spark ML and distributed data processing
  • Experience building predictive models and anomaly-detection algorithms
  • Competency in RAG pipelines, document extraction and AI agents
  • English at Upper-Intermediate (B2) level or above
Qualification wording
Minimum 3 years working in AI/ML engineering and solution delivery
Skilled in Databricks, Spark ML, and distributed data processing systems
Experience creating predictive models and anomaly-detection algorithms
Competency in constructing RAG pipelines, document extraction, and AI agents
English language proficiency at Upper-Intermediate (B2) level or above

Tools in this posting

  • Databricks
Source — Tool mentions in context
We are looking for a Senior AI Engineer who will construct, validate, and implement ML and GenAI components supporting asset onboarding, industrial diagnostics, and device analytics using Databricks. This professional will create predictive models, anomaly-detection algorithms, RAG pipelines, document extraction systems, and AI agent functionalities. Responsibilities Construct, validate, and implement ML and GenAI components using Databricks Design predictive models supporting asset onboarding and device analytics Architect and build anomaly-detection algorithms for industrial diagnostics Develop RAG pipelines that enable intelligent information retrieval Build document extraction workflows handling both structured and unstructured data Create AI agent functionalities that support advanced automation use cases Work with cross-functional teams to convert business requirements into AI solutions Enhance model performance, scalability, and reliability within production environments Track deployed models and refine them based on performance data and user feedback Requirements Minimum 3 years working in AI/ML engineering and solution delivery Strong background in AI Solution Engineering, covering model design and deployment Skilled in Databricks, Spark ML, and distributed data processing systems Experience creating predictive models and anomaly-detection algorithms Competency in constructing RAG pipelines, document extraction, and AI agents Familiarity with GenAI principles and industrial diagnostics applications Ability to architect complete ML workflows spanning data ingestion through deployment English language proficiency at Upper-Intermediate (B2) level or above

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 1, 20262 days ago
Recorded sightings
4
Last seen by us
Nov 4, 2026
Employer says posted
Oct 26, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 6 and day 69.

From 4,296 similar postings that came down. Coming down is not always a hire.

EPAM Systems is hiring

656 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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Has EPAM Systems posted this job before?

Yes. We’ve followed 3 other Senior AI Engineer/ Databricks, Machine Learning jobs there since November 2026. All 3 are still up.

  1. Place not statedStill up after 3 days, first seen Nov 1
  2. Place not statedStill up after 3 days, first seen Nov 1
  3. Place not statedStill up after 3 days, first seen Nov 1
  4. This jobUp 3 days so far, first seen Nov 1

Large employers often post one title for several teams, so these can be separate openings.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

We are looking for a Senior AI Engineer who will construct, validate, and implement ML and GenAI components supporting asset onboarding, industrial diagnostics, and device analytics using Databricks. This professional will create predictive models, anomaly-detection algorithms, RAG pipelines, document extraction systems, and AI agent functionalities. Responsibilities Construct, validate, and implement ML and GenAI components using Databricks Design predictive models supporting asset onboarding and device analytics Architect and build anomaly-detection algorithms for industrial diagnostics Develop RAG pipelines that enable intelligent information retrieval Build document extraction workflows handling both structured and unstructured data Create AI agent functionalities that support advanced automation use cases Work with cross-functional teams to convert business requirements into AI solutions Enhance model performance, scalability, and reliability within production environments Track deployed models and refine them based on performance data and user feedback Requirements Minimum 3 years working in AI/ML engineering and solution delivery Strong background in AI Solution Engineering, covering model design and deployment Skilled in Databricks, Spark ML, and distributed data processing systems Experience creating predictive models and anomaly-detection algorithms Competency in constructing RAG pipelines, document extraction, and AI agents Familiarity with GenAI principles and industrial diagnostics applications Ability to architect complete ML workflows spanning data ingestion through deployment English language proficiency at Upper-Intermediate (B2) level or above
Source details

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