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What You'll Be Doing:
As Engineering inter, you play a key role in sustain and optimize GPU products for better yield, supply and quality on ATE (automatic test equipment) platform
You will be analyze product line dppm & field dppm (defect parts per million) & customer returns Lead detailed data analysis methods to correlate customer failures with internal production data to help understand root cause, risk, and exposure.
Working with multi-functional efforts with design, foundry, quality, test to root-cause problems and implement improvements at ATE level
What We Need To See:
Master studentsin Electrical Engineering/Computer Engineering, Computer Science, or related discipline.
Strength presenting & communicate to technical audiences and methodical problem-solving with critical thinking, solution focused and attention to detail.
We like people who are highly motivated with strong sense of ownership, have excellent interpersonal skills, and high sense of team-work with intellectual honesty
Ways To Stand Out From The Crowd:
Experiences using C++ & python in Linux environment (user and/or kernel modes)
Experience withe data tool with JMP/Excel or R related data analytic tools.
Passionate about experimental work and data evaluation, hunger to get to the bottom of understanding where models fall short in the real world
Demonstrated ability to work in a cross-functional team environment
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