The Role

• AI/ML Infrastructure Management: Architect, deploy, and maintain scalable AI/ML infrastructure leveraging Kubernetes and KFserve for model hosting and management.

• Model Deployment & Optimization: Implement efficient deployment pipelines for AI/ML models, focusing on optimization, scalability, and reliability.

• Performance Monitoring & Tuning: Monitor model performance metrics, identify bottlenecks, and implement improvements to enhance efficiency and accuracy.

• Team Leadership & Collaboration: Lead a small team of engineers, fostering a collaborative environment and ensuring effective communication and knowledge sharing.

• Cross-functional Collaboration: Work closely with data scientists, software engineers, and other stakeholders to understand requirements, translate them into scalable solutions, and ensure successful deployment.

• Continuous Integration/Continuous Deployment (CI/CD): Implement and maintain CI/CD pipelines for AI/ML models to ensure rapid and reliable model updates and releases.

• Documentation & Best Practices: Develop and maintain documentation, best practices, and standard operating procedures related to ML infrastructure and deployment processes.

What we need

• Proficiency in Kserve, Large Language Models (LLMs), Kubernetes, and Flyte for AI/ML model deployment and management.

• Strong background in managing AI/ML infrastructure at scale.

• Experience with CI/CD pipelines for AI/ML models.

• Proven ability to lead and manage small teams effectively.

• Excellent problem-solving skills with a focus on scalability and reliability.

• Strong communication and collaboration skills, ability to work effectively in cross-functional teams.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).