DevOps Engineer - AI/ML Specialist

• Guide research and engineering teams to close knowledge gaps and improve AI model performance in DevOps and infrastructure engineering, cloud platforms, and reliability and observability topics.
• Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to DevOps and infrastructure engineering problems.
• Evaluate DevOps and infrastructure engineering tasks and solutions and provide clear, written technical feedback.
• Build and evaluate realistic infrastructure tasks such as Kubernetes manifests, Terraform modules, CI/CD pipelines, and incident debugging scenarios.
• Develop rubrics to assess infrastructure design, security posture, reliability, and cost tradeoffs.
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Must-Have

• 4+ years of dedicated professional experience in DevOps, SRE, platform, or infrastructure engineering at a recognized, top-tier organization.
• Hands-on production experience with Kubernetes and containers (Docker), and infrastructure as code (Terraform, Pulumi, or CloudFormation).
• Deep experience with at least one major cloud provider (AWS, GCP, or Azure) and CI/CD tooling (GitHub Actions, Jenkins, ArgoCD, or similar).
• Strong scripting skills in Python, Bash, or Go.
• Demonstrable career progression.
• Ability to engage reliably for at least 20 hours/week during weekdays.
• Strong written communication skills and the ability to explain complex technical decisions clearly.

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey.