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Browse remote CI/CD positions — ML pipeline automation, DevOps for AI systems, and deployment engineering roles at AI-first companies.
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Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and...
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Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-de...
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Posted 1 month ago
Senior Forward Deployed Engineer (AI Agent)
Cresta
Taiwan (Remote) · also open in 3 other locations
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform co...
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Rebuild how the world works, to make institutions work better for the people they serve. About Brain Co. Brain Co. builds AI-native operating systems...
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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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