NVIDIA is looking for Deep Learning Software Engineers to develop and productize deep learning solutions in autonomous driving vehicles by applying and developing NVIDIA's deep learning software libraries and hardware architecture.
Requirements
- 2+ years of experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc.)
- Experience with solving a computer vision task using deep neural networks, such as object detection, scene parsing, image segmentation.
- Strong Python and/or C/C++ programming skills
- Proven technical foundation in CPU and GPU architectures, containers (nvidia-docker), numeric libraries, modular software design
- Familiar with CNNs and Transformer architectures
- Experience with low precision inference, quantization, compression of DNNs
- Experience with NVIDIA software libraries such as CUDA and TensorRT
Responsibilities
- Train, fine-tune, optimize and customize perception DNNs in low precision (FP16/INT8)
- Apply sophisticated quantization of DNNs
- Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs
- Continuously improve inference speed, accuracy and power consumption of DNNs
- Stay up to date with the latest research and innovations in deep learning, implement and experiment with new insights to improve NVIDIA's automotive DNNs.
- develop new deep learning architectures
- train deep learning models
Other
- MS or PhD degree in computer science, computer vision, computer architecture or equivalent experience in technical field
- 5+ years of work experience in software development.
- 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.
- Open source project ownership or contribution, healthy GitHub repositories, guiding and/or mentoring experience
