Senior AI Developer Technology Engineer

NVIDIA•Durham, NC

10d•$184,000 - $356,500•Hybrid

About The Position

NVIDIA is seeking a Senior AI Developer Technology (DevTech) Engineer to accelerate generative AI training and inference. The role connects NVIDIA’s platform with developers by working directly on customer projects to improve performance, remove bottlenecks, and support the developer community. The engineer will help advance AI models and influence the future of NVIDIA hardware and software stacks. The position focuses on GPU acceleration and performance optimization across generative AI—including LLMs, diffusion models, and multimodal systems—as well as deep learning and machine learning. The engineer will collaborate with developers, industry and academic experts, and NVIDIA engineering and research teams. Work may also contribute to training and inference frameworks, low-level software libraries, open-source projects, and the design of future hardware, system software, libraries, and programming models. The role includes sharing optimization findings through developer blogs and industry conferences. NVIDIA’s Developer Technology organization identifies market innovations and advances them through NVIDIA products. Its work supports NVIDIA’s leadership in accelerated computing and provides findings to the developer community and guidance to NVIDIA engineering teams.

Requirements

Master’s degree in Computer Science, Computer Engineering, or a related computational field, or equivalent experience.
8+ years of relevant work or research experience in software engineering and performance tuning.
Programming fluency in C/C++ and a deep understanding of algorithms and software development.
Background in accelerated computing, with comprehensive knowledge of parallel programming, performance analysis, and optimization.
Hands-on experience with low-level performance optimizations.
Foundational understanding of modern CPU and GPU architectures.
Good communication and organizational skills, a logical approach to problem solving, and prioritization skills.

Nice To Haves

Expertise in parallelization and performance optimization of LLMs, diffusion models, and multimodal architectures for training and inference.
Experience with training and inference stacks, serving frameworks, and pre-training and post-training pipelines.
Strong foundation in linear algebra and numerical methods.
Continuous learning, proactive engagement with cutting-edge technologies, and adaptability to a rapidly evolving landscape.

Responsibilities

Develop techniques to GPU-accelerate complex workloads across generative AI, deep learning, and machine learning.
Work directly with key developers to optimize and accelerate generative AI training and inference on the NVIDIA platform.
Build and optimize algorithms for performance, and contribute to training and inference frameworks, low-level software libraries, and open-source projects.
Collaborate with technical experts in industry and academia to analyze and optimize AI algorithms on modern CPU and GPU architectures.
Collaborate with NVIDIA engineering and research teams to shape next-generation hardware, system software, libraries, and programming models.
Publish optimization techniques in developer blogs and present them at industry conferences.