Machine Learning Engineer – Ann Arbor, MI

Machine Learning Engineer

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 in 2019 we invested 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
The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.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? Group/Division
The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on improving the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.

Responsibilities

  • Deeply understand the data in the context of KLA business and assess technologies that can be leveraged to generate useful and actionable insights from data to help KLA gain competitive advantage.
  • Provide technology vision to a group of data scientists and software engineers in the field of natural language processing, anomaly detection, classification and/or regression problems, deep learning model architecture, statistical modeling, time series, feature engineering, computer vision, etc.
  • Quickly build a proof of concept machine learning pipeline from data collection, model training, to metrics to evaluate the effectiveness of the proposed methodology.
  • Build a machine learning platform/application for the end-to-end machine learning lifecycle: rapid prototyping; full-scale training; deploying, monitoring, maintaining models; and iterating on modeling ideas based on user feedback.
  • Serve the machine learning model in a stand-alone application or through a robust API
  • Collaborate with other teams to understand their sometimes ambiguous requirements, collect their feedback on machine learning results, and incorporate various signals into the machine learning models.
  • Review codes submitted by junior team members. Mentor junior machine learning engineers.

Qualifications

Required Qualifications

  • Passionate about applied machine learning and deep learning
  • Ph.D. with 3+ years or Masters with 6+ years of software engineering with ML focus
  • Deep understanding of all well-known machine learning algorithms. The candidate should know the assumptions, advantages, limitations of each model and grasp the trade-off when choosing among different models.
  • Hands-on experience with building machine learning models using scikit-learn, Tensorflow, Keras or Pytorch
  • Strong core CS fundamentals (data structures, algorithms, architecting systems).
  • Practical experience with implementing a machine learning system that may mix with heuristic rules, prior knowledge, and other constraints.
  • Proof of record of delivering a machine learning system to generate ROI
  • Ability to solve problems independently, good sense of teamwork and communication skills

Preferred Qualications

  • Experience with Cloud Computing (AWS/Azure)
  • Experience working with open-source software is a plus
  • Understanding of front-end application development. (Javascript, HTML)
  • Hands-on experience with R

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.

Minimum Qualifications

Doctorate (Academic) or work experience of 5 years , Master’s Level Degree or work experience of 6 years , Bachelor’s Level Degree or work experience of 7 years
We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.

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