Implementation Methodology Engineer

NVIDIA is hiring an Implementation Methodology Engineer in Santa Clara, United States. It pays $136k-$219k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
Level classes it as a senior role.
NVIDIA has 2,600+ other open roles on Level.

AI in this role

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.
Develop in house solutions to improve NVIDIA's workflows.
You will collaborate with logic designers, physical designers 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).
5+ years of experience in logic design implementation and/or physical design implementation
Strong automation skills
Good understanding of physical design implementation eg: physical synthesis, placement, routing, logic restructuring, etc.
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 implementation methodology
Proficiency in Python, Tcl, Java, C++ 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 other objective job-related factors. The expected base salary ranges for this position are:
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.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

How we rate this

Implementation Methodology Engineer at NVIDIA rates 14 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.