NVIDIA Networking is looking for an IC Product Engineer (PE) to take ownership of NVIDIA Networking IC mass production engineering and data analysis, and to take part of IC Network Production, Reliability, Validation and Characterization group. You will be a part of a team working on groundbreaking technologies. We are in need of hardworking and motivated engineers. Do you have the passion for data analysis, post-Si hand on work and problem solving? We will be happy to have you on our team!
What You'll Be Doing:
Lead multiple networking ICs’ product engineering activities, which will include making real time decisions on quality of silicon, define pass/fail criteria for screening, solve multi-disciplinary problems and perform cost reduction and quality enhancement, by sophisticated data analysis, AI tools and deep understanding of testing and HW.
You will work closely with both vendors (test houses and fab) and internal engineering teams (operations, IC test, reliability, characterization, package assembly and HW).
You will be working with the best engineers in the field! In an exciting, fast-pace and challenging work environment. Learning new things every day and help improving Nvidia's network products!
We look forward to expand our team ahead of the phenomenal technological developments coming our way.
What We Need to See:
We seek out graduates of Electrical Engineering/Material Engineering/Physics with relevant experience.
2+ years of experience working in or with a manufacturing environment, excellent analytical skills, high ability to identify trends, patterns, and insights from data.
Candidates should be adept at queries, report writing and presenting findings, and be comfortable with data reporting & visualization tools such as PowerBI
We are looking for candidates able to multi-task, engage with other teams members, be attentive to details, proactive and tackle problems quickly.
Workable English skills (verbal and written).
Ways to Stand Out From the crowd:
Experience in semiconductor industry, IC PE activities.
Background in complex and big data/yield analysis.
Experience with AI models.
Experience with UltraFlex or/and other IC test system.
Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python.
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