Are you passionate about driving innovation in deep learning and eager to work on cutting-edge AI technology? Join NVIDIA's TensorRT team as a Software Engineer, and be at the forefront of technology, contributing to high-performance AI inference solutions for specialized platforms and applications. Your fresh perspective and technical skills will help shape the performance and functionality of our products, ensuring NVIDIA remains synonymous with innovation. If you're ready to tackle challenging projects, push the boundaries of AI performance, and make a significant impact in a company that values creativity, excellence, and teamwork, we want to hear from you!
What you'll be doing:
- Contribute to the design and development of high-performance deep learning inference software using modern C++
- Collaborate with teams across the hardware and software stack to understand and leverage new technologies to improve TensorRT's functionality and performance
- Participate in the development of robust, high-quality C++ code in alignment with Modern C++ standards
- Support systematic reasoning about test plans from unit to integration level
- Assist in documenting the properties of functions, classes, and systems to improve robustness
- Contribute to performance optimization and benchmarking efforts
- Help develop new features and capabilities for TensorRT to serve specialized customer needs
What we need to see:
- Masters, or PhD in relevant fields (Computer Engineering, Computer Science, Electrical Engineering, AI) or equivalent experience
- Strong foundational C++ skills, including familiarity with C++11 and C++14 or newer standards
- Familiarity with the C++ Standard Template Library (STL)
- Familiarity with modern deep learning models and inference frameworks
- Interest in performance optimization and systems programming
- Demonstrated ability to take initiative and see projects through to completion
- Excellent interpersonal skills and a collaborative, pragmatic approach to solving problems
Ways to stand out from the crowd:
- Experience with Python and/or CUDA through coursework, internships, or personal projects
- Exposure to systems programming, embedded systems, and/or compiler concepts
- Experience in software performance analysis, profiling, or optimization techniques
- Knowledge of C++17 or later standards
- Understanding of computer architecture, memory management, or parallel computing concepts
