DevOps Expert

• Job Description
• DevOps Expert
• Contractor
• Remote

Job Summary

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities

• Design, implement, and manage robust CI/CD pipelines to automate AI model training and evaluation processes.
• Deploy, monitor, and optimize scalable environments using Kubernetes and Docker on AWS infrastructure.
• Collaborate closely with data scientists and AI engineers to streamline and improve the model development lifecycle.
• Identify and resolve system bottlenecks to enhance performance, reliability, and cost-efficiency.
• Develop and maintain comprehensive infrastructure documentation, fostering knowledge sharing in the team.
• Drive continuous improvements by integrating DevOps best practices tailored for machine learning workflows.
• Ensure the security, compliance, and integrity of cloud-based AI development environments.

Required Skills and Qualifications

• Proven expertise in DevOps methodologies and a track record of success in advanced project environments.
• Hands-on experience with Kubernetes for container orchestration and Docker for containerization.
• In-depth proficiency with AWS services and managing cloud-native infrastructure at scale.
• Exceptional written and verbal communication skills; able to convey complex technical concepts clearly.
• Strong problem-solving skills and the ability to thrive in collaborative, remote-first teams.
• Demonstrated ability to automate infrastructure and streamline workflows for technical teams.
• Proficiency in infrastructure as code (IaC) tools and best practices.

Preferred Qualifications

• Prior experience supporting AI model training, evaluation, or machine learning operations (MLOps).
• Experience optimizing DevOps for data-driven and AI-centric projects.
• Certifications related to AWS, Kubernetes, or DevOps engineering.