HPC Software Manager

HPC Software Manager

KLA is looking for an HPC Software Manager to build and lead a team responsible for architecting and developing the distributed software infrastructure for image computing clusters within the LS division. This pivotal role involves enabling scalable, high-performance platforms that support advanced image processing and AI workloads.

Key Responsibilities

• Strategic Leadership: Define and drive the long-term vision and roadmap for distributed HPC software infrastructure supporting image computing clusters.
• Team Development: Build, mentor, and grow a high-performing team of software engineers and technical leaders.
• Cross-functional Collaboration: Partner with product, hardware, and algorithm teams to align infrastructure capabilities with evolving image processing and AI requirements.
• Platform Architecture: Oversee the design and implementation of scalable, fault-tolerant distributed systems optimized for hybrid CPU/GPU workloads.
• Lifecycle Management: Lead the end-to-end development of image computing platforms, from requirements gathering through deployment and maintenance, using best-in-class project management practices.
• Developer Enablement: Deliver robust software platforms and tools that empower engineers to develop, test, and deploy new image processing and deep learning algorithms efficiently.
• Innovation in Hybrid Computing: Spearhead the integration of traditional image processing and AI/DL techniques into a unified hybrid computing architecture, leveraging modern HPC technologies.

Skills

• Deep understanding of distributed computing frameworks and Linux Systems Programming.
• Proficiency in C++, Python, and/or other systems programming languages.
• Familiarity with GPU computing and hybrid CPU/GPU architectures.
• Strong grasp of software development best practices, CI/CD, and DevOps principles.
• Demonstrated ability to lead and drive functional teams.
• Excellent communication and stakeholder management skills.
• Passion for mentoring and developing engineering talent.
• Proven track record in building and scaling distributed systems, preferably in HPC or cloud-native environments.
• Experience with image processing, computer vision, or AI/ML infrastructure is highly desirable.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field.