Key Skills

Job Description

APPLY DIRECTLY HERE: https://t.mercor.com/nyhF2 Role Overview We are expanding our elite Engineering Expert Network, connecting highly skilled DevOps and Platform Engineers with leading AI research laboratories. In this fully remote consulting role, you will leverage your deep expertise in cloud infrastructure and deployment pipelines to train, evaluate, and refine frontier artificial intelligence models focused on automated system engineering. Core Responsibilities Once matched with an active project, your contributions will include: Training and evaluating AI models on complex DevOps workflows, CI/CD pipelines, and cloud architecture logic. Designing infrastructure tasks, system architecture challenges, and deliverables based on real-world scenarios. Providing domain-specific, structured feedback on AI-generated scripts and deployment strategies to advance automated engineering research. Candidate Profile Robust professional experience in building and maintaining CI/CD pipelines. Deep expertise in cloud infrastructure environments (AWS, GCP, or Azure). Strong hands-on proficiency with containerization and orchestration tools (Docker, Kubernetes). Fluent in written and spoken English, with exceptional communication skills to clearly document technical evaluations. Highly self-motivated with the proven ability to work independently in a remote setting. Engagement Details & Compensation Work Structure: 100% remote, independent contractor position. Set your own flexible hours. Commitment: Typical engagements range from 15 to 30 hours per week, depending on project scope. Compensation: Highly competitive hourly rate. Payments are processed securely and weekly via Stripe or Wise based on services rendered. Confidentiality: Your work will not involve accessing, using, or sharing any confidential infrastructure data or proprietary code from your current employer. Next Steps By applying, you are registering for our continuous Platform Engineering Talent Network. Please submit your resume outlining your cloud and DevOps stack. Verified engineers will undergo a brief AI-guided technical interview and be matched with upcoming projects on a rolling basis. (We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.)

Core Responsibilities

Train and evaluate AI models on DevOps workflows, CI/CD pipelines, and cloud architecture, and design infrastructure tasks based on real-world scenarios. Provide structured technical feedback on AI-generated scripts and deployment strategies to support automated engineering research.

Requirements

Candidates should have substantial experience building and maintaining CI/CD pipelines, deep expertise in AWS, GCP, or Azure, and hands-on proficiency with Docker and Kubernetes. They must communicate fluently in written and spoken English and be able to work independently in a remote setting.