ML Software Engineer

KLA Tencor   •  

Ann Arbor, MI

Industry: Manufacturing

  •  

Less than 5 years

Posted 34 days ago

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

KLA has always had a close relationship with data. Our optical and electron beam inspection and measurement tools use sophisticated data analytic techniques to provide value for our customers.
In this role, you will be part of a world class team of data science researchers, machine learning and application engineers who build and use a world class platform for development of Industrial AI application.
We are looking for engineers with a passion for data science and software engineering who can rapidly incorporate evolving ideas from academia and industry into useful solutions for our internal and external customers.

Responsibilities

  1. Work across the ML development platform (data, training, serving) to directly optimize operational cost through utilization improvements and efficiency work.
  2. Develop insight tooling that would provide cost estimates (training and serving) for various ideas being developed by ML engineers. Unviable ideas can be weeded out early this way.
  3. Design and build capacity management framework to introduce notions of priority into jobs and ensuring that no part of the system is overloaded at any time.

Qualifications

Doctorate (Academic)ORMaster's Level Degree with at least 2 years of experience.ORBachelor's Level Degree with at least 3 years of experience.

Minimum Qualifications

Doctorate (Academic)ORMaster's Level Degree with at least 2 years of experience.ORBachelor's Level Degree with at least 3 years of experience.

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