Software Engineer, TensorRT Specialized Platforms - New College Grad 2025
at Nvidia
USD 124,000-195,500 per year
Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Python @ 3
C @ 3
C++ @ 2
Performance Optimization @ 3
CUDA @ 3
Deep Learning @ 3
AI @ 3
Profiling @ 3
TensorRT @ 3
Performance Analysis @ 3
- 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 driving innovation in deep learning and eager to work on cutting-edge AI technology? Join NVIDIA's TensorRT team as a Software Engineer and contribute 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.
Responsibilities
- 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.
Requirements
- Masters or PhD in a relevant field (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
- 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.
Compensation & Benefits
- Base salary range: 124,000 USD - 195,500 USD (determined based on location, experience, and pay of employees in similar positions).
- Eligibility for equity and benefits (link to NVIDIA benefits).
Additional information
- Applications for this job will be accepted at least until June 2, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering an inclusive work environment.