NVIDIA Networking is excited to announce an outstanding opportunity for an IC Foundry Engineer to join our IC Product Engineering team in Israel. At NVIDIA, we flourish with innovation and modern technology. The ICs are at the forefront of the technology node, leading the industry in early adoption of the most advanced processes.
This position combines complex data analysis of various IC parametric measurements, close work with internal groups from various fields (Build, backend, layout and analog teams, Operations, IC test, Reliability, Characterization etc.) and close interaction with the foundry engineering teams.
This position suits someone passionate about semiconductor manufacturing, yield optimization, and working with world-class teams to deliver flawless performance.
What you'll be doing:
Drive yield and performance improvements across advanced nodes.
Serve as the key interface between NVIDIA and foundry partners, leading technical communication and driving issues to full containment.
Collaborate in a matrix structure and multiple domains for comprehensive product optimization.
Develop and apply data pipelines to identify yield limiters and process excursions.
Build automated monitoring and alerting frameworks to proactively detect process drift.
What we need to see:
B.Sc. in Electrical Engineering, Materials, Physics, Chemical Engineering, or equivalent experience.
5+ years of proven experience in Process, Integration, Device engineering, or Semiconductor manufacturing.
Strong knowledge of FAB processes, integration flows, device behaviour, and quality metrics.
Outstanding problem-solving and data analysis skills.
Experience with large datasets and correlation methodologies.
Ability to multitask, prioritize, and complete tasks under pressure.
Strong communication and presentation skills.
High ownership, autonomy, and accountability.
Familiarity with scripting/programming (Python or similar) for data analysis and workflow automation.
Passion for data systems, automation, and applying AI/ML techniques to engineering problems.
Ways to stand out from the crowd:
Experience working directly with FAB or Silicon technology supporting systems (inspection tools, OSAT, etc.).
Hands-on experience with data analysis tools (e.g., JMP).
Experience with visualization tools (e.g., Tableau, custom Python dashboards).
Experience building or using ML models for yield prediction, defect classification, or process control.
Familiarity with data platforms or semiconductor-specific data ecosystems.
Skills Required
- B.Sc. in Electrical Engineering, Materials, Physics, Chemical Engineering, or equivalent experience.
- 5+ years of experience in Process, Integration, Device engineering, or Semiconductor manufacturing.
- Strong knowledge of FAB processes, integration flows, device behaviour, and quality metrics.
- Outstanding problem-solving and data analysis skills.
- Experience with large datasets and correlation methodologies.
- Ability to multitask, prioritize, and complete tasks under pressure.
- Strong communication and presentation skills.
- High ownership, autonomy, and accountability.
- Familiarity with scripting/programming (Python or similar) for data analysis and workflow automation.
- Passion for data systems, automation, and applying AI/ML techniques to engineering problems.
- Experience working directly with FAB or silicon technology supporting systems (inspection tools, OSAT, etc.).
- Hands-on experience with data analysis tools (e.g., JMP).
- Experience with visualization tools (e.g., Tableau, custom Python dashboards).
- Experience building or using ML models for yield prediction, defect classification, or process control.
- Familiarity with data platforms or semiconductor-specific data ecosystems.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
