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Remote CI/CD Jobs

Browse remote CI/CD positions — ML pipeline automation, DevOps for AI systems, and deployment engineering roles at AI-first companies.

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MLOps Engineer DevOps for AI CI/CD Platform Engineer ML Automation Engineer Infrastructure Engineer

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Jobs & Projects

Baseten

Posted 3 months ago

Engineering Manager, Cloud Platform

Baseten

San Francisco

Full-time
English
$165K – $330K / year
spark ci/cd kubernetes machine learning machine learning
Full page
Cerebras

Posted 3 months ago

Staff Software Engineer, GPU Inference

Cerebras

Toronto, CAN

staff
Full-time
English
Full page
Baseten

Posted 3 months ago

Cloud Platform Engineer

Baseten

San Francisco

Full-time
English
$165K – $330K / year
spark ci/cd kubernetes machine learning machine learning
Full page
Poolside

Posted 3 months ago

Member of Engineering (Infrastructure)

Poolside

Remote (EMEA)

Full-time
English
Full page
Baseten

Posted 3 months ago

Security Engineer

Baseten

San Francisco

Full-time
English
$150K – $250K / year
Full page
Cerebras

Posted 3 months ago

AI Inference Core - Senior Senior Software Engineer for DevOps

Cerebras

Sunnyvale, CA

senior
Full-time
English
Full page
Cerebras
lead
Full-time
English
Full page
Cerebras

Posted 3 months ago

DevOps Engineer - New Grad 2026

Cerebras

Toronto, CAN

Full-time
English
Full page
Cohere
Full-time
English
C$215K – C$385K / year
Full page
Harvey

Posted 3 months ago

Senior Software Engineer, Backend Core Infra

Harvey

Bengaluru

senior
Full-time
English
Full page

Role guide

What to expect in remote CI/CD jobs

CI/CD for AI is more complex than standard software — it requires validating not just code, but data, models, and system behaviour. Remote CI/CD jobs at AI companies involve building automated testing and deployment pipelines for ML systems, implementing model regression testing, and ensuring AI products ship reliably. Engineers who bridge DevOps and ML system knowledge are in consistent demand.

What you'll work on

  • Build automated ML testing pipelines that prevent broken models reaching production
  • Design deployment workflows that ship AI updates in minutes, not days
  • Implement shadow mode testing to safely validate new model versions on live traffic
  • Create infrastructure-as-code environments for reproducible AI development

What companies look for

  • CI/CD platform experience — GitHub Actions, GitLab CI, CircleCI, or Jenkins
  • ML-specific testing — data validation, model regression, integration testing
  • Blue/green and canary deployment strategies for safe ML model releases

Frequently asked questions

What remote CI/CD jobs are available at AI companies?

MLOps and DevOps engineering roles where CI/CD for ML systems is a core responsibility. Most require Docker and cloud platform experience (AWS, GCP, or Azure) alongside CI/CD pipeline knowledge.

What makes CI/CD for ML different from regular software CI/CD?

ML pipelines must validate data quality, model performance metrics, and integration behaviour — not just code correctness. Engineers design test suites that catch data drift, model degradation, and integration failures automatically.

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