DevOps Engineer for AI Model Training

• Contribute to training and evaluating AI models that require DevOps and platform engineering expertise.
• Create tasks and deliverables that reflect real world engineering scenarios.
• Provide domain specific feedback to improve frontier AI research and model behavior.
• Work independently on remote projects, following client and project requirements., * Typical project time commitment varies, commonly 15 to 30 hours per week, projects vary in scope and duration.
• Matching to projects happens on a rolling basis as opportunities become available.

• Professional experience with CI/CD pipelines.
• Experience managing cloud infrastructure on AWS, GCP, or Azure.
• Familiarity with containerization and orchestration tools, such as Docker and Kubernetes.
• Strong verbal and written communication skills.
• Ability to work independently in a remote environment.

Hourly rate range, 70 to 150 per hour. Rates depend on project scope and your experience. Eligibility and How to Join

• This is an open application to join the talent network. Completing the application does not guarantee immediate placement.
• Application steps, complete your profile by uploading your resume and confirming your work location, then complete the required AI interview.
• Verification process, credentials and interview results are reviewed to approve qualified experts for matching.
• Once approved, you become eligible for project matches. When a suitable project is available, you may be invited to interview for that specific opportunity.
• If selected, you will work remotely on a contract basis and earn competitive hourly rates according to the project agreement.