Specialist, Software Technology

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Enabling the movement towards advanced chip design, KLA's Global Products Group (GPG), which is responsible for creating all of KLA's metrology and inspection products, is looking for the best and the brightest research scientist, software engineers, application development engineers, and senior product technology process engineers. First to deliver the best imaging and classification data for every defect or point on any layer at any time. EBeam's mission encapsulates its role as the eyes of KLA's product line, providing timely information on defects and critical locations on the wafer at the highest spatial resolution possible. Customers use EBeam products alongside KLA patterned and bare wafer inspectors to quickly understand the nature of defects and other imperfections on product wafers and take action to correct the manufacturing process.

Job Description/Preferred Qualifications

Must have Qualifications:

• Deep proficiency in core programming concepts, with hands-on expertise in Java, Python, or C++
• Strong background in object-oriented design (OOD) and multi-threaded application development
• Demonstrated experience in full-stack web development, specializing in microservices architecture, performance optimization, and security best practices
• Solid understanding of data structures and algorithms
• Practical experience with Kubernetes and designing scalable microservices
• Excellent analytical, problem-solving, and organizational skills, with strong communication abilities (both verbal and written)
• Ability to bridge theoretical concepts and real-world implementations
• Experience managing the full product development lifecycle, from concept to deployment
• Experience designing and deploying ML/DL pipelines for training, inference, validation, and monitoring is a plus
• Technical leadership or mentoring experience is a plus
• Exposure to computer vision, signal processing, or timeseries analysis, particularly for highvolume or highresolution data is a plus

Responsibilities:

• Design, develop, and maintain ML/DLbased software solutions & big-data analysis for large, complex semiconductor systems
• Apply machine learning and deep learning techniques to semiconductor metrology, inspection, yield analysis, defect classification, and process optimization
• Collaborate with globally distributed teams, including hardware, optics, algorithms, and systems engineers, to deliver highimpact AI solutions
• Analyze and resolve complex systemlevel issues spanning software, ML models, data quality, and hardware interactions
• Drive model performance tuning, robustness, and explainability to meet manufacturing and customer requirements
• Identify root causes of product or process variability and propose innovative MLdriven solutions
• Support technology transfer from research and prototyping to highvolume manufacturing environments
• Travel to other company sites and customer locations as required to support deployment, debugging, and adoption
• Participate in endtoend product development lifecycle activities, from design through deployment and support

Minimum Qualifications

Doctorate (Academic) Degree and related work experience of 3 years Master's Level Degree and related work experience of 6 years Bachelor's Level Degree and related work experience of 8 years

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