Job details

Research Scientist - Noise Reduction Algorithms

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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

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. The Surfscan group includes a team of engineers, technology development, apps engineers and product marketing focused on technology that enables wafer, IC and equipment manufacturers to develop, qualify and monitor their process tools. Defects and process non-uniformities detected on Surfscan equipment allow for early identification of yield excursions. The flagship Surfscan products include the SPx platforms for wafer surface quality and wafer defect inspection tools and systems for inspection of polished wafers, epi wafers and engineered substrates during the wafer fabrication process.

Job Description/Preferred Qualifications

Responsibilities

This is a R&D position in the advanced technology group for the SurfScan division, focusing on developing new methods of noise reduction for the future generations of un-patterned wafer inspection tools.

Research new concepts and algorithms to suppress noise in wafer inspection systems.
Develop statistical models to quantify performance improvements.
Validate concepts through modeling, implementation, and data testing.

Qualifications

Doctorate (Academic) in Machine Learning with experience in Image Processing
Experience with Computational Imaging
Solid understanding of Physics of light material interactions and Optical image formation theory.
Strong background in mathematics, statistics, image processing, and machine learning.
Proficient in programming and data analysis.
Innovative, technically broad and solidly grounded

Minimum Qualifications

Doctorate (Academic) in Machine Learning with experience in Image Processing AND
Bachelor's Level Degree or Master's Level Degree in Physics OR Optics

Base Pay Range: $130,400.00 - $221,700.00 Annually

Primary Location: USA-CA-Milpitas-KLA

KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including 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, and family care and bonding leave.

Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.

KLA is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, national origin, sex, gender identity, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other status protected by applicable law. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us at talent.acquisition@kla.com or at +1-408-352-2808 to request accommodation.

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.

Average salary estimate

$176050 / YEARLY (est.)

min

max

$130400K

$221700K

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What You Should Know About Research Scientist - Noise Reduction Algorithms, KLA

At KLA, we're on the hunt for a passionate Research Scientist specializing in Noise Reduction Algorithms to join our dynamic team in Milpitas, CA. If you're excited about innovation and working with cutting-edge technology, this position will let you dive into the fascinating world of semiconductor manufacturing. In this role, you’ll focus on developing advanced noise reduction methods for un-patterned wafer inspection tools, vital for improving the functionality and quality of the next generation of electronic devices. You'll be at the forefront of research, exploring new concepts and algorithms, validating them through rigorous modeling and data testing. Your expertise in machine learning, image processing, and statistical modeling will play a key role in our mission of delivering precise and effective solutions for our partners. KLA prides itself on nurturing a collaborative environment—each day presents a thrilling challenge as we tackle complex problems that push the boundaries of technology. If you hold a doctorate in machine learning with experience in image processing, and have a strong grasp of optical image formation theories, we want to meet you. Join us and help shape the future of the semiconductor industry while enjoying a workplace that values creativity, innovation, and personal growth.

Frequently Asked Questions (FAQs) for Research Scientist - Noise Reduction Algorithms Role at KLA

What are the primary responsibilities of a Research Scientist - Noise Reduction Algorithms at KLA?

As a Research Scientist focused on Noise Reduction Algorithms at KLA, your primary responsibilities will include researching new concepts and algorithms specifically designed to suppress noise in wafer inspection systems. You will also develop statistical models to quantify performance improvements and validate these concepts through thorough modeling, implementation, and data testing.