AI Operations Engineer; MLOps

Our client is seeking a skilled AI Operations Engineer (MLOps) to join their high-performing, fully remote team. This role is dedicated to building and maintaining the infrastructure and pipelines necessary for the efficient development, deployment, and monitoring of machine learning models. You will play a key part in streamlining the end-to-end ML lifecycle, ensuring reliability, scalability, and reproducibility. This is a critical position for driving operational excellence in AI.

• Design, implement, and manage robust CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for training, deploying, and serving ML models at scale.
• Implement monitoring solutions to track model performance, drift, and operational health in production.
• Automate ML workflows, data pipelines, and model retraining processes.
• Collaborate with data scientists and software engineers to troubleshoot and resolve operational issues.
• Ensure security, compliance, and best practices are followed throughout the ML lifecycle.

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in Dev Ops, SRE, or MLOps roles.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, Git Lab CI, Git Hub Actions).
• Familiarity with scripting languages (e.g., Python, Bash) and infrastructure-as-code tools (e.g., Terraform, Ansible).
• Understanding of machine learning concepts and workflows.

• Competitive salary and comprehensive benefits package.
• Fully remote work arrangement with flexible scheduling.
• Opportunity to work with cutting-edge MLOps technologies and practices.
• Generous paid time off and holidays.
• Professional development budget for courses and conferences.
• Supportive team environment focused on collaboration and innovation.