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DevOps Engineer - AI/ML Specialist

Role overview

Summary

This role focuses on enhancing AI model performance through DevOps and infrastructure engineering. You will collaborate with research and engineering teams at Mercor, providing guidance and technical feedback while developing infrastructure solutions.

Qualifications

  • 4+ years of professional experience in DevOps, SRE, platform, or infrastructure engineering.
  • 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.
  • Strong scripting skills in Python, Bash, or Go.
  • Strong written communication skills and the ability to explain complex technical decisions clearly.

Responsibilities

  • Guide research and engineering teams to improve AI model performance in DevOps and infrastructure engineering.
  • Design domain-relevant tasks and write structured solutions to engineering problems.
  • Evaluate tasks and solutions, providing clear technical feedback.
  • Build and evaluate infrastructure tasks such as Kubernetes manifests and CI/CD pipelines.

Key facts

Hard skills

Other skills

  • Communication

About the company

Mercor logo

Mercor

  • Job Boards & Talent Marketplaces
  • 51–200
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

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Job description

About the job

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.

Position: DevOps / Infrastructure Engineer
Type: Contract
Compensation: $80–$120/hour
Location: Remote

Role Responsibilities

  • 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.

Qualifications

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.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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