Analyst, Algorithm Development Engg (CUDA)

Company Overview 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.

Group/Division Enabling the movement toward advanced chip design, KLA's Measurement, Analytics and Control group (MACH) is looking for the best and brightest research scientists, software engineers, application development engineers and senior product technology process engineers to join our team. The MACH team's mission is to collaborate with our customers to innovate technologies and solutions that detect and control highly complex process variations—at their source—rather than compensate for them at later stages of the manufacturing process. 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. Our MACH team develops leading-edge solutions for patterning process analytics and control technologies, thereby providing customers with critical insight at the feature level, field level and cross-wafer analysis. Our teams also develop advanced modeling simulation, data analytics and process control modeling technologies. As a member of the MACH team, you’ll be joining the most sophisticated and successful process-control company in the semiconductor industry--working across functions to solve the most complex technical problems in the digital age.

Job Description/Preferred Qualifications Key Responsibilities

• Develop algo focusing on CUDA acceleration, CPU to GPU conversion of image processing algos and models
• Stay updated with emerging technologies and industry best practices. Bring new ideas to the team by exploring modern frameworks or tools that could enhance the platform’s capabilities.

Required Qualifications

• Education: Master’s degree in Computer Science or a related field, or Bachelor’s degree in Computer Science (or related) with at least 3 years of hands-on as CUDA algo engineer.
• Experience: Minimum 3+ years of professional algo development experience focusing on CUDA acceleration, CPU to GPU conversion of image processing algos and models. Proven track record of delivering software projects from design to deployment.
• Programming Skills: Deep understanding of operating systems, computer networks, and high performance applications. Good mental model of the architecture of a modern distributed systems that is comprised of CPUs, GPUs, and accelerators. Experience with deployments of deep-learning frameworks based on TensorFlow, and PyTorch on large-scale on-prem or cloud infrastructures. Strong background in modern and advanced C++ concepts. Strong Scripting Skills in Bash, Python, or similar.Good communication with the ability to write clean, efficient, and well-documented code.
• Team Collaboration: Strong communication skills and ability to work effectively in a cross-functional team setting. Comfortable collaborating with diverse team members (developers, testers, domain experts) and conveying technical ideas clearly.
• Adaptability: A willingness to learn new technologies and adapt to evolving project requirements. Enthusiasm for working in a dynamic, fast-changing environment where priorities may shift as the project grows

Preferred Qualifications (Nice-to-Haves)

• HPC/Simulation Background: Experience working on projects involving scientific computing, simulations, or HPC applications. Familiarity with parallel computing concepts or engineering simulations (CFD, FEA, etc.) can help in understanding the platform’s context
• DevOps & CI/CD: Hands-on experience with DevOps tools and workflows. Knowledge of setting up CI/CD pipelines using platforms like Azure DevOps, Jenkins, or GitHub Actions to automate build and deployment processes
• Containerization & Cloud: Experience with container technologies (Docker) and orchestration (Kubernetes) for deploying microservices is a plus. Familiarity with cloud services or infrastructure (Azure, AWS, etc.) for scalable deployment environments

Minimum Qualifications Master’s degree in Computer Science or a related field,

or Bachelor’s degree in Computer Science (or related)

with at least 3 years of hands-on as CUDA algo engineer. We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees. KLA is proud to be an equal opportunity employer Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA’s Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to talent.acquisition@kla.com to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.