Nvidia Corporation in
Senior Software Engineer, Deep Learning - Torch-TRT
Nvidia Corporation in, Santa Clara, California, us, 95053
Senior Software Engineer, Deep Learning - Torch-TRT (Finance)
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing – an era in which our GPU acts as the brains of computers, robots, and self‑driving cars that can understand the world. As an NVIDIA employee, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are looking for outstanding Senior Deep Learning Software Engineers to develop and productize NVIDIA’s deep learning solutions in autonomous driving vehicles. In the Solution Engineering – Automotive Machine Learning team, we are developing new technologies that allow more capable deep learning models to be deployed in physical AI systems. As part of this role, you will develop compiler technology to allow larger and better models to be optimized for NVIDIA’s unique hardware architecture, and you will be exposed to the pressing problems our partners face during product development. You will coordinate with other architecture and software teams to develop the best solutions for partners working on our platforms.
What you’ll be doing:
Developing compiler technologies to run various classes of model architecture (Transformer, Diffusion, VLA, CNN, RNN, etc.) on NVIDIA hardware, leveraging techniques such as reduced precision, quantization, workload scheduling and memory bandwidth optimization.
Working across the entire lifecycle of a model: training, fine‑tuning, and optimization to allow customers to access pioneering models on NVIDIA hardware.
Developing workflows that let users leverage frameworks (e.g., PyTorch, JAX) and ecosystem tools (HuggingFace, MLIR) without forgoing performance.
Staying current with the latest research and innovations in deep learning, implementing and experimenting with new insights to improve NVIDIA’s Physical AI DNNs.
What we need to see:
MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in a technical field.
5+ years of software development experience.
2+ years of experience implementing deep learning models and optimizations such as graph fusions, kernel implementation, KV caching, etc.
Domain experience in current innovative deep learning methods (e.g., diffusion models, vision‑language action models, etc.).
Strong Python and/or C/C++ programming skills.
Proven technical foundation in CPU and GPU architectures, containers (nvidia‑docker), numeric libraries, and modular software design.
Willingness to take action and strong analytical skills.
Excellent time‑management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into sophisticated projects.
Ways to stand out from the crowd:
Background with low‑precision inference, quantization, and compression of DNNs.
Experience optimizing GPU workloads or developing kernels for common DL operators.
Experience with NVIDIA software libraries such as CUDA and TensorRT.
In‑depth experience with the internals of deep learning frameworks such as PyTorch or JAX (e.g., creating custom operators, graph fusions, deploying PyTorch models).
Experience using current‑generation kernel‑authoring DSLs such as Triton or cuTile or similar.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer you and your family at
https://www.nvidiabenefits.com/ .
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $184,000–$287,500 for Level 4, and $224,000–$356,500 for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until December 16, 2025.
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal‑opportunity employer. We do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
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We are looking for outstanding Senior Deep Learning Software Engineers to develop and productize NVIDIA’s deep learning solutions in autonomous driving vehicles. In the Solution Engineering – Automotive Machine Learning team, we are developing new technologies that allow more capable deep learning models to be deployed in physical AI systems. As part of this role, you will develop compiler technology to allow larger and better models to be optimized for NVIDIA’s unique hardware architecture, and you will be exposed to the pressing problems our partners face during product development. You will coordinate with other architecture and software teams to develop the best solutions for partners working on our platforms.
What you’ll be doing:
Developing compiler technologies to run various classes of model architecture (Transformer, Diffusion, VLA, CNN, RNN, etc.) on NVIDIA hardware, leveraging techniques such as reduced precision, quantization, workload scheduling and memory bandwidth optimization.
Working across the entire lifecycle of a model: training, fine‑tuning, and optimization to allow customers to access pioneering models on NVIDIA hardware.
Developing workflows that let users leverage frameworks (e.g., PyTorch, JAX) and ecosystem tools (HuggingFace, MLIR) without forgoing performance.
Staying current with the latest research and innovations in deep learning, implementing and experimenting with new insights to improve NVIDIA’s Physical AI DNNs.
What we need to see:
MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in a technical field.
5+ years of software development experience.
2+ years of experience implementing deep learning models and optimizations such as graph fusions, kernel implementation, KV caching, etc.
Domain experience in current innovative deep learning methods (e.g., diffusion models, vision‑language action models, etc.).
Strong Python and/or C/C++ programming skills.
Proven technical foundation in CPU and GPU architectures, containers (nvidia‑docker), numeric libraries, and modular software design.
Willingness to take action and strong analytical skills.
Excellent time‑management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into sophisticated projects.
Ways to stand out from the crowd:
Background with low‑precision inference, quantization, and compression of DNNs.
Experience optimizing GPU workloads or developing kernels for common DL operators.
Experience with NVIDIA software libraries such as CUDA and TensorRT.
In‑depth experience with the internals of deep learning frameworks such as PyTorch or JAX (e.g., creating custom operators, graph fusions, deploying PyTorch models).
Experience using current‑generation kernel‑authoring DSLs such as Triton or cuTile or similar.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer you and your family at
https://www.nvidiabenefits.com/ .
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $184,000–$287,500 for Level 4, and $224,000–$356,500 for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until December 16, 2025.
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal‑opportunity employer. We do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
#J-18808-Ljbffr