KLA is looking to solve complex, high-impact challenges in the semiconductor industry, specifically in image processing, computer vision, and defect detection for state-of-the-art inspection systems.
Requirements
- 5+ years of hands-on experience in image processing, computer vision, or machine learning in a production environment
- Deep expertise in spectral/spatial filtering, model-based methods, and inverse problem solving
- Strong proficiency in C++, with experience developing on Linux platforms
- Proven ability to prototype and validate algorithms in Python or MATLAB
- Familiarity with CUDA, TensorFlow, or other GPU-accelerated frameworks is a strong plus
- Experience architecting algorithms from the ground up and solving real-world vision challenges at scale
- Strong understanding of computer vision and image processing concepts
Responsibilities
- Design and optimize cutting-edge algorithms for image processing, inverse problems, and computer vision
- Prototype in Python or MATLAB, and implement high-performance solutions in C++ on Linux
- Accelerate algorithm performance using CUDA/GPU programming
- Collaborate with systems, software, and hardware teams to translate complex requirements into scalable solutions
- Lead technical discussions, mentor junior engineers, and contribute to long-term algorithm strategy
- Architect, optimize, and lead the development of advanced algorithms that push the boundaries of what’s possible in high-resolution imaging and real-time analysis
- Work closely with cross-functional teams to define technical direction, validate performance, and ensure seamless integration into production systems
Other
- 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
- Ability to work in a hybrid work model with 3 days in the office and flexibility built in
- Strong communication and collaboration skills to work with cross-functional teams
- Ability to grow impact through technical leadership, cross-functional collaboration, and continuous learning
- Must be eligible to work in the USA
