Description
We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will work on building world-class 3D obstacle perception solutions based on multi-sensor fusion, including cameras, ultrasonic sensors, and radar, to estimate high-resolution reconstruction of the world. The primary approach will be deep learning.
Your key responsibilities will include:
- Developing deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios.
- Identifying and analyzing the strength and weakness of the developed 3D obstacle perception solutions using large-scale benchmark data (both real and synthetic) and improving them iteratively through KPI building and optimization.
- Productizing the developed 3D obstacle perception solutions by meeting product requirements for safety, latency, and software robustness, with a strong emphasis on production deep learning model development.
- Driving and prioritizing data-driven development by working with large data collection and labeling teams to bring in high-value data to improve perception system accuracy.
To succeed in this role, you will need:
- 10+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real-world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).
- Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly in high-resolution world reconstruction.
- Proven experience in production deep learning model development, including careful data verification, model architecture design, loss function engineering, and debugging ML models.
- Experience in data-driven development and collaboration with data and ground truth teams.
- Strong programming skills in Python and/or C++.
- Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other.
If you have experience on end-to-end deep learning model development, proven expertise in developing perception solutions for autonomous driving or robotics using deep learning with multi-sensor input, or hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real-time applications, you will stand out from the crowd.