Senior Developer Technology Engineer - Windows AI Platform

at Nvidia

USD 184,000-356,500 per year

SENIOR

✅ On-site

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 API @ 4 CUDA @ 4 Communication @ 6 Debugging @ 4 GPU @ 6 GenAI @ 4 LLM @ 4 Profiling @ 4 Python @ 7 Technical Leadership TensorRT @ 4

Details

NVIDIA is working to define the next era of computing by advancing AI and accelerated computing technologies. As a Developer Technology Engineer, you will collaborate with industry partners, internal engineering and product teams, and open-source software projects to drive adoption of AI and accelerated computing on the NVIDIA RTX platform.

Responsibilities

Work with internal engineering and product teams and external application developers to solve local, end-to-end AI GPU deployment challenges on the NVIDIA RTX AI platform.
Use profiling and debugging tools to analyze demanding GPU-accelerated AI applications, identify insufficient GPU utilization, and improve runtime performance.
Conduct hands-on training, develop sample code, and deliver presentations providing guidance on efficient end-to-end AI deployment targeting optimal runtime performance on NVIDIA ARM-based SoCs.
Improve the Windows LLM and GenAI user experience on NVIDIA RTX through feature and performance enhancements to open-source software, including GGML, Llama.cpp, Ollama, and ONNX Runtime.
Collaborate with GPU driver, architecture, and research teams to influence next-generation GPU features using real-world workflows and feedback from partners and customers.
Provide technical leadership and mentorship to junior engineers while supporting an inclusive, high-performing team environment.
Travel as needed for conferences and on-site visits with external partners.

Requirements

8 or more years of professional experience in local GPU deployment, profiling, and optimization.
Bachelor's or Master's degree, or equivalent experience, in Computer Science, Engineering, or a related field.
Strong proficiency in C/C++, Python, software design, and programming techniques.
Familiarity with and development experience on the Windows operating system.
Experience working with open-source LLM and GenAI software.
Experience with CUDA and NVIDIA's Nsight GPU profiling and debugging suite.
Strong problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
Excellent interpersonal and communication skills, with a passion for keeping up with advances in AI technology.

Preferred Qualifications

Experience with GPU-accelerated AI inference using NVIDIA APIs, specifically cuDNN, CUTLASS, and TensorRT.
Expert knowledge of Vulkan and/or DirectX 12.
Detailed knowledge of the latest-generation GPU architectures.
Experience with AI deployment on NPUs and ARM architectures.

Benefits

The base salary range is USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5, determined by location, experience, and compensation for similar positions. The role is also eligible for equity and benefits.