Senior Systems Engineer, Neural Graphics

Reposted 15 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
224K-431K Annually
Expert/Leader
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior Neural Graphics Scientist will define NVIDIA's Neural Graphics strategy, pioneer neural shading techniques, connect research to products, drive AI innovations, and influence hardware design.
Summary Generated by Built In

Computer graphics is undergoing its most significant transformation since the invention of the GPU. AI and traditional rendering are converging, opening unprecedented possibilities for real-time visual experiences. At NVIDIA, our Neural Graphics team is where ground breaking techniques meet production systems used by millions of developers and creators worldwide. Through technologies like AlpaDreams — our neural world simulation system delivering neural-reconstruction-level fidelity in open worlds — we're solving the hardest integration and performance challenges at the frontier of AI and graphics. This is systems work — understanding the full problem, making sharp design trade-offs, and building something that holds together end-to-end under real-world constraints.

We're looking for an outstanding engineer to be a driving force in this evolution. You'll bring deep expertise in graphics and AI to our production team, taking novel techniques and driving them through the hard last-mile engineering required to ship real products. You see research and engineering as the same work at different altitudes — and you're motivated by the systems optimization, integration challenges, and steadfast iteration that turn a promising idea into something millions of people use. If that sounds like you, this is an outstanding opportunity to shape the future of visual computing.

What You'll Be Doing:
  • Take innovative world simulation techniques — like AlpaDreams — and drive them into production-ready, real-time pipelines integrated with downstream stacks

  • Own the end-to-end path from prototype to shipping product — performance optimization, system integration, quality bar

  • Solve the hard systems challenges — latency, memory, throughput — that stand between a research demo and a product customers depend on

  • Make principled design trade-offs across the full stack — choosing the right level of complexity, identifying where a simpler approach wins, and understanding how decisions in one stage affect the rest of the pipeline

What We Need to See:
  • Degree in Computer Science, Computer Graphics, Machine Learning, or equivalent practical experience

  • 12+ years of experience with a sustained track record of shipping impactful products or technologies

  • Experience taking research concepts through the full lifecycle to production-quality systems

  • Systems-level thinking — you naturally reason about end-to-end behavior, cross-cutting concerns, and why a design works, not just that it works

Ways to Stand Out:
  • Hands-on work with world models, diffusion models, LLMs, neural radiance fields, differentiable rendering, or neural content generation in shipped products or production pipelines

  • Experience building scalable systems with AI agents

  • Non-traditional background bringing fresh, interdisciplinary approaches (e.g., computational physics, materials science, game engine development)

  • A track record of turning ambitious research into technology that actually works at scale

  • You think like a systems architect — you can articulate why a design decision was made, what alternatives were considered, and what trade-offs were accepted

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 12, 2026.

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

  • Degree in Computer Science, Computer Graphics, Machine Learning, or equivalent experience
  • 12+ years of proven experience with technical contributions
  • Extensive knowledge of real-time rendering, neural networks, and physics simulation
  • Track record of successful technology transfers from research to shipping products

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.

  • 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.
  • 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.
  • 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

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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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