AI Software Engineer

Base Pay Range: $65,200.00 - $110,800.00 Annually

Primary Location: USA-MI-Ann Arbor-KLA

KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits identified below. Interns are eligible for some of the benefits identified below. Our pay ranges are determined by role, level, and location. The range displayed above reflects the minimum and maximum pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including location, job-related skills, experience, and relevant education level or training. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.

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. Central Engineering is KLA's largest engineering organization comprised of 9 Centers-of-Excellence (CoE) in various disciplines applied across all product groups in the company. These CoE include Handling & Automation, Precision Motion Control, Sensors & Image Acquisition, Platform Design, and Packaging Engineering, among others. Talent includes over 500 engineers across global centers in Israel, China, India, and the US. Each CoE contributes not just talent and deliverables per discipline toward product programs, but also subject matter expertise, best practices, roadmaps, specialized facilities, apparatus, models, and analytics. These differentiate KLA not only in WHAT we do, but also in HOW we do it.

Job Description/Preferred Qualifications

Responsibilities

Software Engineers in the AI and Physics Modeling team may work on a variety of tasks including platform for large scale experimentation, scale out of physics models, data management and inference solutions for KLA products. 

Although familiarity with Machine Learning and Deep Learning solutions would be a big plus, this is primarily a Software Engineering position.  Successful candidates are passionate about software and will have exceptional skills and hands-on experience with development in C/C++ and Python in a Unix environment.  Deep conceptual understanding of multi-threaded and multi process software systems is also necessary.

In addition to the above fundamental software skills, any of the following technical hands-on skills are highly desirable:

System Programming and Operating Systems.

Distributed systems for data management.

Distributed computing infrastructure.

Cloud technologies for storage, containerization, and compute clusters.

Data Structures and algorithms.

GPU architectures and data management.

Traditional machine learning using Random Forest, XG Boost, Logistic Regression.

Deep Learning for regression, classification.  Generative models.

TensorFlow, NumPy, scikit-learn, and other ML and DL frameworks.

MPI and similar distributed computing framework.

GPU Architectures and CUDA (CuGraph, CuData, CuML etc).

GO Systems Programming, Java Programming.

Successful candidates for this position will a