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. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, 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 to allow more capable deep learning models to be deployed in Physical AI systems. As part of the role, you will develop compiler technology to allow larger and better models to be optimized to leverage NVIDIA’s unique hardware architecture. You will also be exposed to the most pressing problems that our partners face during product development and coordinate with other architecture and software teams to develop the best solution 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 whole lifetime of a model: training, fine-tuning, optimization to allow customers to access pioneering models on NVIDIA hardware
Develop workflows that let users leverage frameworks (e.g. PyTorch, JAX) and ecosystem tools (HuggingFace, MLIR) without forgoing performance
Stay up to date with the latest research and innovations in deep learning, implement and experiment 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 technical field
5+ years of work experience in software development.
2+ years of experience in 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, modular software design
Willing to take action and have strong analytical skills.
Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects.
Ways to stand out from the crowd:
Background with low precision inference, quantization, compression of DNNs
Experience optimizing GPU workloads and 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, deployment of 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 to you and your family 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 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.