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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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At Zowie, we build AI agents that handle millions of real conversations every month, for brands like InPost, Empik, Decathlon, and Allianz. They track...
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Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By making better use...
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Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By making better use...
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Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By making better use...
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Build AI contracting at enterprise scale. Ship it fast. Ironclad is building AI on one of the most consequential datasets in enterprise software: over...
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Build AI contracting at enterprise scale. Ship it fast. Ironclad is building AI on one of the most consequential datasets in enterprise software: over...
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Siena is the Agent of Record for CX, built for consumer brands like Spanx, FIGS, Brooklinen, and Grüns. It runs as a connected multi-agent stack on to...
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We are rebuilding biotech for the AI era. When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop fr...
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Posted 3 weeks ago
Software Engineer in Network Infrastructure
Nebius
Amsterdam, Netherlands; Remote - Europe
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers...
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We are rebuilding biotech for the AI era. When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop fr...
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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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