Senior AI-Native Systems Software Engineer, TensorRT

Posted 2 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
Hybrid
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Build NVIDIA’s AI-native TensorRT framework using agentic workflows and multi-agent orchestration. Architect scalable systems for AI-generated software, prototype state-of-the-art deep learning capabilities, and deliver high-performance inference for language, diffusion, audio, vision, and multimodal models. Optimize Python orchestration and C++ engine implementations for latency and throughput while translating customer needs into production-quality solutions.
Summary Generated by Built In

Are you passionate about redefining how software is built in the age of Generative AI? Join NVIDIA’s TensorRT team to help lead a first-of-its-kind, AI-native initiative designed to make TensorRT the default entry point for out-of-framework inference globally. We are moving beyond traditional development cycles with a new framework built from the ground up to leverage swarms of AI agents to produce high-performance, high-quality, modern C++ software at an unprecedented scale.

If you are a systems-thinking C++ engineer who wants to help scale out an agentic development framework, stay on top of state-of-the-art deep learning breakthroughs, and improve users’ experience with lightning-fast model onboarding, we want to hear from you!

What you'll be doing:

  • Architecting an AI-native framework: Help design and build a codebase and architecture that scales beyond human capacity, supporting large numbers of AI agents working in parallel to generate, test, and validate production-grade software.

  • Scaling through agentic workflows: Improve the ratio of compute-to-software output by adopting and building AI-native tools, multi-agent orchestrators, and codebase harnesses that keep humans focused on the highest-value work..

  • Rapid prototyping with SOTA models: Act as a technical scout, identifying industry and academic breakthroughs (e.g., new attention mechanisms, KV cache strategies) and dispatching AI agent swarms to prototype and integrate these capabilities into our framework.

  • Delivering a great user experience: Ensure a seamless, high-performance path to production for the latest model families (LLMs, Diffusion, Audio, Vision and multi-modal models).

  • Extreme performance optimization: Work at the intersection of Python orchestration and C++ engine-level optimizations to achieve major latency and throughput gains for critical customer use cases.

What we need to see:

  • BS, MS, or PhD in Computer Science, Computer Engineering, AI, or equivalent experience.

  • 4+ years of relevant software development experience.

  • Strong modern C++ skills: Proficiency with C++11/14/17 (or newer) and the STL, with an emphasis on clean, maintainable, performant code.

  • Deep learning familiarity: Experience with modern inference frameworks and an understanding of the architectural nuances of LLMs, Diffusion, and multi-modal models.

  • Systems thinking: Interest in how software architecture must evolve to support automated, agent-driven development and indefinitely scaling codebases.

  • End-to-end product sense: Ability to translate high-level customer needs into concrete technical requirements and user-centric solutions.

  • Pragmatic execution: Demonstrated ability to go from customer requests to production-quality software on tight timelines.

  • Collaborative mindset: Excellent communication skills and comfort working across internal organizations and with customers.

Ways to stand out from the crowd:

  • Agentic framework experience: Hands-on work with AI agent orchestrators or multi-agent coding frameworks, or experience building custom agentic coding harnesses for production software.

  • CUDA & kernel expertise: Experience with CUDA programming or exposure to kernel generation / autotuning efforts.

  • High-velocity prototyping: A track record of rapidly turning state-of-the-art papers into working prototypes in days, not weeks.

  • Performance profiling skills: Expertise in software performance analysis, profiling, and optimization (CPU and/or GPU), including using tooling to drive measurable wins.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous, and love a challenge, come join our team and help us build the future of high-performance AI inference technology!

#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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 30, 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.

Skills Required

  • Bachelor’s, master’s, or PhD in Computer Science, Computer Engineering, AI, or equivalent experience
  • 4+ years of relevant software development experience
  • Strong modern C++ skills, including C++11/14/17 or newer and the STL
  • Experience with modern inference frameworks and familiarity with LLM, diffusion, and multimodal model architectures
  • Interest in software architecture for automated, agent-driven development and indefinitely scaling codebases
  • Ability to translate customer needs into technical requirements and user-centric solutions
  • Ability to deliver production-quality software on tight timelines
  • Excellent communication skills and ability to collaborate across organizations and with customers
  • Experience with AI agent orchestrators, multi-agent coding frameworks, or production agentic coding harnesses
  • CUDA programming or kernel generation and autotuning experience
  • Track record of rapidly prototyping state-of-the-art research into working software
  • Expertise in CPU or GPU performance analysis, profiling, and optimization

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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