We are looking for an Implementation Methodology Engineer to join NVIDIA VLSI team. If you are looking for a challenging and exciting role and you are a self-starter and highly motivated individual who loves to collaborate and find solutions to hard technical problems, join us today!
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to pursue, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today.
What you’ll be doing:
You will be responsible for all aspects of front-end design implementation methodologies (synthesis, formal-equivalence-checking), flow automation and application support.
Use NVIDIA implementation flows and EDA tool expertise to improve power, performance and area on NVIDIA's most critical designs
You will collaborate with logic designers, physical designers and EDA vendors to solve exciting implementation issues and develop new solutions.
Provide support for EDA tools and flows
What we need to see:
BS or MS in Electrical Engineering, Computer Engineering, or related fields (or equivalent experience).
4+ years of experience in logic design implementation and/or physical design implementation
Deep understanding of logic optimization techniques and relative area, timing, and power trade-offs
Strong understanding of physical design implementation eg: physical synthesis, placement, routing, logic restructuring, etc.
Should be a power user of synthesis and/or place and route EDA tools from Synopsys (DC/FC), Cadence (Genus/Innovus)
Good debugging and problem-solving skills
Strong interpersonal skills along with the ability to work in a dynamic team
Ways to stand out from the crowd :
Prior experience in physical implementation
Proficiency in Python, Tcl, Make scripting
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and dedicated people in the world working for us. Are you creative and autonomous? Do you love the challenge of constant innovation and creating the highest performance products in the industry? If so, we want to hear from you. Come, join NVIDIA VLSI team and help build the real-time, cost-effective computing platform driving our success across multiple fields such as Deep Learning and AI, Robotics and Autonomous Driving, Gaming and High Performance Computing.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.Skills Required
- BS or MS in Electrical Engineering, Computer Engineering, or related fields
- 4+ years of experience in logic design implementation and/or physical design implementation
- Deep understanding of logic optimization techniques and timing, area, and power trade-offs
- Strong understanding of physical design implementation techniques
- Proficiency with EDA tools from Synopsys and Cadence
- Good debugging and problem-solving skills
- Strong interpersonal skills and team collaboration
- Prior experience in physical implementation
- Proficiency in Python, Tcl, Make scripting
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.”
