As a Component Engineer at NVIDIA, you will play a key role in enabling robust, scalable, and efficient hardware builds. You will identify, qualify, and support the most suitable component solutions for NVIDIA products. Responsibility includes understanding the supplier and component landscape, assessing technical and supply‑chain risks, and supporting teams that build products throughout the full product lifecycle. This role is central to ensuring component quality, availability, longevity, and strict compliance with NVIDIA processes.

What You Will Be Doing:

• Partner with hardware, mechanical, firmware, software, supply chain, quality, and reliability teams to understand requirements and trade-offs
• Evaluate, qualify, and approve components and suppliers across technologies and product lines
• Review specifications and alternatives to balance performance, cost, reliability, and lifecycle
• Drive component selection, including sourcing strategy and second-source approval
• Support teams through development, validation, ramp, and production
• Own component data in PLM systems, ensuring accuracy and compliance
• Identify and mitigate risks related to PCNs, EOLs, and long-term supply
• Use data and AI tools to improve analysis and decision-making
• Improve tools, processes, and best practices in component engineering

What We Need to See:

• Bachelor’s degree in Electrical Engineering or equivalent experience
• 5+ years of experience in component engineering or related work
• Strong understanding of electronic components and their use
• Experience reviewing datasheets and technical documentation
• Familiarity with qualification, validation, and reliability practices
• Experience with PLM systems (e.g., Agile / PDP or similar)
• Ability to work independently and take ownership
• Strong problem-solving skills with a practical mindset
• Ability to use AI tools in day-to-day work

Ways to Stand Out of the Crowd:

• Ability to learn quickly and adapt to new technologies or domains
• Creative thinking and comfort working in ambiguity
• Experience influencing decisions across teams
• Track record of improving processes, tools, or ways of working