Senior Software Engineer, Deep Learning Inference
NVIDIA
At NVIDIA, we're at the forefront of innovation, driving advancements in AI and machine learning to solve some of the world’s most challenging problems. We're seeking talented and motivated engineers to join our TensorRT team in developing the industry-leading deep learning inference software for NVIDIA AI accelerators.
As a Senior Software Engineer in the TensorRT team, you will be responsible for designing and implementing inference optimizations to enable real-time AI applications on personal computing devices with NVIDIA AI accelerators (GPU, DLA). You will work closely with cross-functional teams to integrate and deploy AI solutions in production environments and your expertise will help shape the performance, functionality and efficiency of our AI models and systems. If you're ready to take on challenging projects and make a significant impact in a company that values creativity, excellence, and collaboration, we want to hear from you!
What you’ll be doing:
Design, implement and optimize TensorRT components to achieve tightly coordinated and responsive Generative AI inference applications for PCs and workstations.
Develop software in C++, Python, CUDA, and DirectML to accelerate systems that enable seamless and efficient deployment of next-gen AI models.
Collaborate with deep learning experts and GPU architects throughout the company.
What we need to see:
BS, MS, PhD or equivalent experience in Computer Science, Computer Engineering or a related field.
5+ years of software development experience on a large codebase or project.
Strong proficiency in C++ and Python programming languages.
Experience with development of: Deep Learning Frameworks, Compilers, or System Software.
Foundational knowledge of Machine Learning techniques or GPU optimizations.
Excellent problem-solving skills and the ability to learn and work effectively in a fast-paced, collaborative environment.
Strong communication skills and the ability to articulate complex technical concepts.
Ways to stand out from the crowd:
Experience in developing DirectML backend for GPU or NPU.
Windows application and middleware development using DirectX or DirectML API.
Knowledge of GPU programming using CUDA or OpenCL.
Experience with deploying AI models in production environments.
Knowledge of additional performance optimization tools and techniques as well as contributions to open-source projects or publications in relevant areas.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.