Algorithm Engineer - Deep Learning

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 Broadband Plasma Division (BBP) provides market-leading patterned wafer optical inspection systems for leading-edge IC manufacturing. Logic, foundry, and memory customers depend on BBP products to detect yield-critical defects for process debug and excursion monitoring at advanced process nodes. BBP flagship products include the 29xx and 39xx series which leverage Broadband Plasma technology to capture a wide range of defects with ultimate sensitivity at the optical inspection speeds needed for inline defect monitoring.

Job Description/Preferred Qualifications

We are looking for a full-time Deep Learning Algorithm Engineer who is passionate about pioneering Deep Learning (DL), foundation models, and GenAI for image processing and computer vision applications in the semiconductor process control business.

Qualified candidates are expected to have a strong background and in-depth experience in deep learning, especially in object detection, segmentation, vision foundation models, and multimodal models. Candidates should also have a deep understanding of relevant theory and hands-on experience grounding DL/GenAI models in real application domains, with strong emphasis on performance, efficiency, and deployment.

The ideal candidate can work independently across the full deep learning project lifecycle, including conceptualizing, exploring, designing, implementing, optimizing, and deploying models. Responsibilities for this position include, but are not limited to:

• Understand state-of-the-art (SOTA) deep learning and GenAI models.

• Connect SOTA DL modeling approaches to domain problem statements.

• Analyze modeling requirements based on product feature requirements.

• Design deep learning and GenAI models to meet modeling requirements.

• Implement modeling prototypes and perform analysis.

• Perform model training and/or tuning on domain datasets.

• Evaluate and validate model performance against defined metrics.

• Analyze model performance bottlenecks.

• Design and optimize DL model architectures, including new modules, efficient backbones, and model compression techniques (e.g., distillation).

• Optimize DL or GenAI model throughput and cost, including mixed-precision and low-precision inference and training (e.g., FP16, FP8).

• Work and communicate collaboratively with peers.

• Present ideas, concepts, and results in professional technical settings.

Qualifications/Education Desired

• Ph.D. in Electrical Engineering, Computer Science, or related quantitative fields.

• Academic or industrial experience applying deep learning or GenAI to real-world problem(s), with impactful results.

• In-depth experience developing and optimizing deep learning, Vision Foundation Models (VFM), or Vision Language Models (VLM) in at least one of the following areas: computer vision, image processing, robotics, NLP, or equivalent, with strong emphasis on efficiency, scalability, and deployment performance.

• Required experience with DL model optimization/distillation for mixed or reduced precision (e.g., FP16, FP8) to improve throughput, latency, and deployment efficiency.

• Experience with GenAI coding tools, vibe coding, or vibe engineering.

• Proficiency in Python and one additional programming language from: C++, Java, Rust, Go.

• Proficiency in at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX, or equivalent).

• Demonstrated deep learning expertise via technical publications in top conferences (e.g., NeurIPS, CVPR, ICML, ICLR, KDD, SIGGRAPH, etc.) and/or industrial patents and/or impactful open-source projects is required.

• Travel required: up to 10%.

• Experience in semiconductor process control is a plus.

Minimum Qualifications

• Doctorate (academic) degree with 0 years of related work experience; or Master’s degree with 3 years of related work experience.

• Academic or industrial experience applying deep learning or GenAI to real-world problem(s), with impactful results.

• Required experience with DL model optimization/distillation for mixed or reduced precision (e.g., FP16, FP8) to improve throughput, latency, and deployment efficiency.

• Travel required: up to 10%.

Base Pay Range: $136,300.00 - $231,700.00 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 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 [email protected] 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 [email protected] to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.