Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
C @ 7
C++ @ 7
CUDA @ 4
Communication @ 6
Deep Learning @ 7
GPU
GenAI
Generative AI
LLM
Performance Analysis
Performance Optimization
Profiling
Python
Software Development @ 6
TensorRT
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
Requirements
- 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!