KLA Sr Platform Engineer- GenAI 

United States, Michigan, Ann Arbor 

841074477

Qualifications

• Identify and resolve infrastructure gaps to ensure reliable, efficient, and scalable solutions
• Develop advanced AI/ML infrastructure solutions that enhance the efficiency of our skilled ML teams
• Design and implement solutions for critical areas, including distributed storage systems, scheduling systems, high availability capabilities, and core reliability issues within our large-scale GPU clusters
• Monitor and optimize the performance of our AI/ML infrastructure, ensuring high availability, scalability, and efficient resource utilization
• Develop and deploy automation tools, monitoring solutions, and operational strategies to streamline infrastructure management and reduce manual tasks
• Work with various teams, including ML developers, data engineers, and DevOps professionals, to create a cohesive and integrated AI/ML infrastructure ecosystem
• Implement and manage GPU infrastructure within Kubernetes clusters to support high-performance computing and AI/ML tasks
• Deploy and manage open-source GenAI components, such as vector databases and various AI/ML models, ensuring seamless integration and optimal performance
• Evaluate and integrate new open-source GenAI tools and technologies to enhance the platform’s capabilities
• Collaborate with the research and development teams to implement and optimize innovative AI/ML models and algorithms
• Ensure the security and compliance of open-source GenAI components within the infrastructure
• Leverage High-Performance Computing (HPC) experience to optimize and manage large-scale AI/ML workloads
• Design, implement, and manage on-premises, cloud, and hybrid-based ML platforms to support diverse AI/ML workloads and ensure flexibility and scalability

Minimum Qualifications

• Bachelor's Degree or equivalenttraining/certificationsin Computer Science or related IT field
• Eight (8) years of implementing and maintaining AI/ML Infrastructure On-Prem environment
• Strong experience with AI/ML infrastructure and tools, including GPU clusters and Kubernetes
• Proficiency in deploying and managing open-source GenAI components and vector databases
• Hands-on experience with high-performance computing (HPC) environments
• Expertise in designing and managing on-premises, cloud, and hybrid-based ML platforms
• Solid understanding of distributed storage systems, scheduling systems, and high availability capabilities