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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

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Posted 3 weeks ago

Forward Deployed Engineer - Japan

Cursor

Japan

Full-time
English
python machine learning ci/cd typescript
Full page
Wayve

Posted 3 weeks ago

Staff Machine Learning Engineer - Ops

Wayve

London, United Kingdom

staff
Full-time
English
Full page
Wayve

Posted 3 weeks ago

Application Software Engineer - Embedded Software C++

Wayve

Sunnyvale, California USA

Full-time
English
$210K – $238K / year
Full page
Wayve

Posted 3 weeks ago

Engineering Manager, App SW - Embedded

Wayve

Sunnyvale, California USA

Full-time
English
$276K – $294K / year
Full page
Airbyte
Full-time
English
C$101K – C$110K / year
Full page
Astronomer
senior
Full-time
English
Full page
Runpod

Posted 3 weeks ago

Director, Security

Runpod

Remote - USA

executive
Full-time
English
Full page
Lambda

Posted 3 weeks ago

Senior Software Engineer - SDN

Lambda

San Francisco Office (Fremont St)

senior
Full-time
English
$266K – $395K / year
Full page
Snowflake

Posted 3 weeks ago

Staff Technical Program Manager - AppEx

Snowflake

US-CA-Menlo Park

staff
Full-time
English
$194K – $278K / year
Full page
Hex

Posted 3 weeks ago

Engineering Director, AI Engineering

Hex

San Francisco

executive
Full-time
English
$300K – $425K / year
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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