As a DevOps Engineer, you’ll apply your expertise in cloud infrastructure, automation, deployment, and platform engineering to contribute to projects focused on training and improving next-generation AI systems. You’ll work with realistic, production-style technical scenarios and help evaluate the quality, reliability, and reproducibility of technical solutions.
No prior AI experience is required. Your DevOps and infrastructure expertise is what matters most.
Key Responsibilities
Design realistic DevOps tasks based on production-style scenarios involving CI/CD, containers, Kubernetes, infrastructure as code, monitoring, and incident response.
Develop working reference solutions with clear setup, implementation, and validation steps.
Review AI-generated technical solutions, identify errors or failures, and provide accurate corrections with clear reasoning.
Evaluate technical work for correctness, reliability, consistency, and reproducibility.
Provide structured feedback to improve future technical tasks and evaluations.
Apply practical DevOps expertise to cloud infrastructure, automation, deployment, and troubleshooting challenges.
Maintain a high standard of technical quality across assigned work.
Required Qualifications
3+ years of professional experience in DevOps, SRE, Platform Engineering, or Infrastructure Engineering.
Strong programming ability in Python, Go, Bash, or TypeScript .
Hands-on experience with CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins.
Practical experience with Docker and Kubernetes .
Experience working with at least one major cloud platform, including AWS, GCP, or Azure .
Strong Infrastructure as Code experience with Terraform, Ansible, Pulumi, or CloudFormation .
Advanced knowledge of Linux and Git .
Strong troubleshooting, analytical, and problem-solving skills.
Excellent written and spoken English.
Availability of at least 20 hours per week .
Preferred Qualifications
Experience with observability platforms such as Prometheus, Grafana, Datadog, or OpenTelemetry .
Background in security, secrets management, or platform reliability.
Open-source contributions or technical writing experience.
Previous experience with AI training data, model evaluation, or technical evaluation projects.
Why Apply?
This is an opportunity to put your DevOps expertise to work on challenging, production-style technical problems while contributing to the development of next-generation AI systems. You’ll work remotely, apply your existing engineering knowledge, and contribute to high-quality technical evaluation and infrastructure work.
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