Product Quality Engineer
NVIDIA
Product Quality Engineer
NVIDIA
Designs the chips and software that power AI
We are looking for a talented Product Quality Engineer (PQE) with 3+ years of technical experience in the semiconductor industry. The candidate will be responsible for automating failure analysis from the NPI phase of the product life cycle through EOL. The primary objective is to collaborate with cross-functional teams to manage and resolve customer complaints and escalations for the chip devices. Moreover, the candidate will also need to support root cause identification and drive corrective action implementation.
What you'll be doing:
Implement quality control procedures and standards.
Analyze product specifications and ensure compliance with industry standards.
Conduct inspections and tests on products to identify defects or issues.
Collaborate with engineering and cross-functional teams to resolve quality issues.
Monitor and report on quality performance and trends.
Provide support to team members on quality standards and procedures.
Continuously improve quality processes and practices.
Cover test tools bring-up, maintenance, and sustaining product activities.
Share lessons learned from previous field quality issues; give early input via DFMEA to ensure known quality, reliability, and production issues are identified, and risks are mitigated
What we need to see:
BS Degree or MS Degree in Electrical or Computer Engineering or a related field.
At least 3 years of experience in product quality / test engineering or a similar role.
Strong knowledge of quality control principles and practices.
Experience with quality management systems and tools.
Excellent problem-solving and analytical skills.
Strong communication and teamwork abilities.
Attention to detail and a commitment to excellence.
Ways to stand out from the crowd:
Good knowledge of CPU / SoC / Automotive products and standards is a plus.
Hands-on expertise in scripting languages such as C / C++ / Linux code
Expertise in Automatic Test Equipment (ATE Tester) and Socket Board test programming for ICFA troubleshooting.
Hands-on experience with the use of lab tools like CSAM, IR, Elite, EDS etc
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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