Product System Engineer

Reposted 2 Days Ago
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Hiring Remotely in México
Remote
Mid level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead cross-functional engineering teams at contract manufacturers to resolve production quality issues, perform root-cause analysis and test planning, own test infrastructure and onsite support, train CM technicians, perform production audits, and analyze test data to drive product yield and reliability improvements.
Summary Generated by Built In

NVIDIA is looking for a Hardware Engineer for our System Product Engineering group. The candidate will take full responsibility for networking systems’ product engineering matters in the CM's (Contract Manufacturing ) production line. The position requires an understanding of hardware, firmware/software, mechanical integration and manufacturing. The candidate will supervise Product engineering activities in a few contract manufacturing lines, working closely with groups across the networking organization: Hardware/Software/Firmware R&D, Architecture, Test Engineering, Quality & Reliability, and Operations groups. The candidate will take part in direct communications with NVIDIA internal and external groups. The position provides an opportunity to gain deep knowledge of NVIDIA networking systems and a system-level view of our solutions, along with working in dynamic and positive environment.

The position require working physically in the CM site.

What you'll be doing:

  • Leading Cross-Organizational Task Forces: You will be responsible for managing and leading multi-functional teams to address quality events and failure modes in NVIDIA's networking products. This involves coordinating efforts from various departments, such as hardware, software, and manufacturing, to collectively work towards identifying and resolving issues.

  • Root Cause Analysis and Test Planning: You will perform in-depth root cause analysis by meticulously analyzing failure modes Monitor and control the test yield for all stations.

  • Onsite engineering support: you will be the technical owner for all tests issues, test infrastructures and tests setup and will have to deliver fast and professional response for all issues.

  • The working place base at factory in FXN Guadalajara Mexico

  • Working and training the CM technicians and working with the CM management - issues when needed

  • Filtering all technical issues as tier2 and leading all production gaps until closure and leading technical task forces until the root cause is found

  • Performing production line audits, making sure the CM is working acc to NV requirements and procedures

  • Data analysis knowledge ( JMP )and working with test logs ( python code understanding )

What we need to see:

  • B.S.C in Electrical Engineering, or equivalent experience.

  • 4+ years of technical experience in hardware design/system

  • failure analysis/debugging/Architecture or Product Engineer.

  • Familiar with the manufacture processes of electric product.

  • Proficient with lab equipment and lab setups and solving skills.

  • A highly motivated teammate who always stays up-to-date with new technologies and FA methodologies.

  • Proficient English is required.

Ways to stand out from the crowd:

  • Experience as a test engineer or product engineer.

  • Experience in board design/system.

  • Familiar with ICT / JTAG technology and/or functional tests.

  • Linux operating systems, and programming languages such as Perl/Python

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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