SW Algorithm Engineer
About The Position
The SW Algorithm Engineer will advance business priorities by developing high-impact algorithms for complex image and signal processing applications. The role focuses on designing, developing, and optimizing machine learning and deep learning algorithms, including taking them from concept and prototyping through production deployment. The engineer will develop computer vision approaches for challenging real-world datasets, analyze system performance, debug issues, and improve production robustness and accuracy. The position works closely with software, systems, applications, and field engineering teams and contributes to decisions and improvements in algorithm architecture, performance, scalability, and maintainability. The position is within KLA’s Semiconductor Products and Customers business unit, specifically the LS-SWIFT division. LS-SWIFT develops high-throughput patterned wafer inspection systems for semiconductor manufacturing, supporting defect detection across advanced packaging, logic, memory, and automotive applications.
Requirements
- Strong background in one or more of machine learning, deep learning, computer vision, or image processing.
- Hands-on experience with at least one major deep learning framework, such as TensorFlow or PyTorch.
- Experience training, validating, and deploying machine learning or deep learning models in production environments.
- Programming skills in C++ and/or Python, with experience in object-oriented and/or functional programming.
- Ability to design model architectures, customize loss functions, and optimize performance for real-world constraints.
- Strong problem-solving skills and ability to work on ambiguous, open-ended challenges.
- Doctorate degree with 0 years of related work experience, master's degree with 3 years of related work experience, or bachelor's degree with 5 years of related work experience.
Nice To Haves
- Experience with large-scale, high-resolution image data or industrial inspection systems.
- Familiarity with performance optimization, GPU acceleration, or real-time systems.
- Experience working in cross-functional product environments from R&D to customer deployment.
Responsibilities
- Design, develop, and optimize machine learning and deep learning algorithms for complex image and signal processing applications.
- Own algorithm development from concept and prototyping through production deployment.
- Invent, evaluate, and implement computer vision approaches for challenging real-world datasets.
- Analyze system performance, debug complex issues, and improve robustness and accuracy in production environments.
- Collaborate with software, systems, applications, and field engineering teams to deliver high-quality solutions.
- Contribute to architectural decisions and improve algorithm performance, scalability, and maintainability.
Benefits
- Medical, dental, vision, life, and other voluntary benefits.
- 401(k) with company matching.
- Employee stock purchase program (ESPP).
- Student debt assistance.
- Tuition reimbursement program.
- Development and career growth opportunities and programs.
- Financial planning benefits.
- Wellness benefits, including an employee assistance program (EAP).
- Paid time off and paid company holidays.
- Family care and bonding leave.
- Performance incentive programs may be available.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
