NVIDIA is now looking for a Senior Technical Program Manager to join our DFX engineering team and lead the software methodology programs that make our chips testable, debuggable, and manufacturable at scale — across infrastructure, implementation, verification, and silicon bring-up! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence.
We serve as the central program management function for NVIDIA’s VLSI Engineering organization, providing the structure and insight needed to deliver world-class silicon. We align roadmaps across all silicon product lines, enabling technical leads to focus on engineering while we accelerate end-to-end execution! Through the integration of domain-specific workflows and intelligent infrastructure, we deliver automated schedule tracking, resource planning, and program health visibility across the full lifecycle—from Arch/RTL handoff through silicon bring-up and productization.
What you'll be doing:
In this role, you will work closely with DFX software and methodology engineers, development managers, and multi-functional partners to lead methodology programs and process improvements from concept through adoption.
- Lead the end-to-end program lifecycle for DFX software methodology across infrastructure, implementation, verification, and bring-up — from requirements and specification through release, adoption, and continuous improvements
- Build and lead roadmaps, schedules, and dependencies for DFX flow, tool, and infrastructure releases, aligning methodology drops to chip program milestones through development, tapeout, fab out, and bring-up
- Drive the release and deployment process for DFX flows and tooling: version planning, regression and quality gates, migration paths, and user adoption across design teams
- Collaborate with engineering teams to define requirements and document architecture, interfaces, and workflows; participate in key design reviews and handle scope changes efficiently
- Coordinate license, and data infrastructure needs with CAD and IT partners so methodology programs scale with the portfolio
- Lead verification and validation planning for methodology — pattern coverage, regression health, and sign-off criteria — and support silicon bring-up by prioritizing lab and field debug tooling needs
- Proactively identify technical, resource, and schedule risks; develop mitigations in partnership with engineering, and provide clear status to leadership with recommendations that support tough trade-offs
- Build metrics and dashboards for methodology health, adoption, and efficiency; capture takeaways, and drive process improvement through automation
What We Need To See
- BS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience (advanced degree a plus)
- 8+ years of combined experience, built on a software engineering or computer science foundation, including a minimum of 3 years of technical program management experience
- Solid understanding of the ASIC/SoC design, verification, and bring-up/productization flow, and a clear understanding of where DFX fits: DFT insertion, scan/ATPG/MBIST, pattern verification, ATE and in-system test, and post-silicon debug
- Experience managing software, tooling, or methodology programs — release cycles, quality gates, infrastructure dependencies, and user adoption — not just implementation schedules
- Strong collaborative and interpersonal skills, specifically a proven track record to effectively guide and influence within a dynamic environment
- Deep understanding of technology and passionate about what you do, with excellent judgment, strong problem solving skills, and strong communication — written and verbal
- Understands and deals well with rapid development cycles and constant change; remains flexible and calm in the face of uncertainty
Ways To Stand Out From The Crowd
- Familiarity with DFX methodologies is a strong plus
- Proven experience scripting and automating tasks; proficiency in Python preferred
- Knowledge of APIs and data analytics for program management and metrics dashboards
- A track record of mentorship — bringing engineers or emerging program managers up to speed on methodology and program execution
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence.
#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 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.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 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.Skills Required
- Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience
- 8+ years of combined experience with a software engineering or computer science foundation
- At least 3 years of technical program management experience
- Understanding of ASIC/SoC design, verification, bring-up, and productization flows
- Understanding of DFX, including DFT insertion, scan, ATPG, MBIST, pattern verification, ATE, in-system testing, and post-silicon debug
- Experience managing software, tooling, or methodology programs, including release cycles, quality gates, infrastructure dependencies, and user adoption
- Strong collaboration, interpersonal, communication, judgment, and problem-solving skills
- Ability to work effectively in rapid development cycles and changing environments
- Advanced degree
- Familiarity with DFX methodologies
- Experience scripting and automating tasks, preferably with Python
- Knowledge of APIs and data analytics for program management and metrics dashboards
- Mentorship experience for engineers or emerging program managers
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.”
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