KLA Careers

Image Processing & Machine Learning Researcher

Company Overview

Calling the adventurers ready to join a company that's pushing the limits of nanotechnology to keep the digital revolution rolling. At KLA, we're making technology advancements that are bigger—and tinier—than the world has ever seen.

Who are we?  We research, develop, and manufacture the world's most advanced inspection and measurement equipment for the semiconductor and nanoelectronics industries. We enable the digital age by pushing the boundaries of technology, creating tools capable of finding defects smaller than a wavelength of visible light. We create smarter processes so that technology leaders can manufacture high-performance chips—the kind in that phone in your pocket, the tablet on your desk and nearly every electronic device you own—faster and better. We're passionate about creating solutions that drive progress and help people do what wouldn't be possible without us.  The future is calling. Will you answer?


We’re transforming the digital age by enabling the manufacture of ICs at next generation technology nodes - 5 & 7 nm design rules. This is done by pushing the boundaries of optics, sensors, image processing, machine learning and computing technologies, creating systems capable of finding defects as small as 10 nm at data rates of 50 GB/second. If you are passionate about driving R&D in advanced deep learning, 3D sensor fusion, Bayesian & Physics based Machine Learning, advanced Neural & HPC architectures, then come join over 500 PhD researchers working at KLA. We actively collaborate with research institutes all over the world with our R&D centers in the San Francisco Bay Area, Shanghai, Tel-Aviv and Chennai. Our corporate office is located in Silicon Valley, Milpitas, California.

 Get more details about KLA from a recent presentation given by our Senior Fellow,

Kris Bhaskar, at the 2016 Neuro-Inspired Computation Elements Workshop:



Categories of R&D Openings

Deep Learning Researcher: These positions will focus on research areas to drive investigations in open areas such as architectures for Unsupervised Outlier Detection, Semi-supervised deep learning for process control applications with stationary and non-stationary signals, as well as feature extraction discovery. The ideal candidate should preferably have a Ph.D. in Bayesian Machine Learning or related areas with extensive software skills to build and research machine learning systems.

Physics Based Machine Learning Researcher: These positions will focus on exploring research in building architectures to exploit explicit knowledge of physics, sensor fusion and associated prior knowledge with Bayesian based generative models to solve problems in building predictive detection of systematic and quasi-random events in semi-conductor manufacturing. Ideal candidates should have a computational physics, chemistry or biology background combined with deep interest and knowledge of Bayesian approaches to machine learning with extensive software skills to build and research machine learning systems.

Image Processing & Machine Learning Researcher: These positions will focus on exploring research in the areas of image processing and computer vision with the aim of building automated machine vision systems in a range of application areas from semi-conductors to satellite scene analysis to driverless cars. The ideal candidate should have a PhD in the related areas of Image Processing, Computer Vision with an emphasis on Bayesian based machine learning with extensive software skills to build and research machine learning systems.

Deep Learning HPC Architectures & Data Systems Engineers: These positions will explore research and development for novel HPC architectures to enable ultra-high performance training and inference on very high bandwidth streaming video data. The ideal candidate should have an MS or PhD in HPC architectures, Hardware Data Flow architectures and practical proven experience in building both scale-in and scale-out systems with familiarity of both SIMD as wells GP-GPU architectures.  The person should also have a keen interest in the deep learning application space with the ability to map complex deep neural architectures to practical system implementations.


Minimum Qualifications

Doctorate (Academic) with at least 2 years of experience. OR Master's Level Degree with at least 4 years of experience. OR Bachelor's Level Degree with at least 5 years of experience.

Equal Employment Opportunity

KLA is an Equal Opportunity Employer. Applicants will be considered for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristics protected by applicable law.

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