Senior Component Engineer
Posted 18 days ago · 37 applicants
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The role in plain words
This role involves identifying, qualifying, and approving component solutions for hardware builds throughout their full product lifecycle. You will partner with cross-functional teams to review specifications, manage component data in PLM systems, and mitigate risks related to component end-of-life or supply issues. Additionally, you will use data and AI tools to improve decision-making and component engineering processes.
- 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
- 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
Extracted from the job description · kept up to date automatically
Who this suits
This role suits individuals with a Bachelor's degree in Electrical Engineering or equivalent experience, and at least 5 years of experience in component engineering. It is less ideal for those who lack experience with PLM systems or are uncomfortable working independently to manage supplier and technical risks.
Full job description
Original listing · kept for referenceAs 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
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Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 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