Prediction Engineer, Autonomous Driving
At Ridecell View All Jobs
Ridecell (www.ridecell.com) is powering next generation of ridesharing, carsharing and autonomous shared mobility services. As the world shifts to a mobility on- demand model and new companies rush to enter as service providers, Ridecell is ready to support these initiatives. Already 20+ customers, including Penske, Renault, RideKleen, Blu Smart and AAA use our proven platform to build their shared mobility businesses.
Using cameras to make sense of the environment around a self driving car is critical. Apply for this role to solve the computer vision problem for self driving cars - detecting and localising road users, debris, driveable space, construction zones, traffic lights and much more. You will be responsible for developing, training and improving deep learning networks for computer vision as well as providing inputs to the sensor fusion and the obstacle path prediction modules.
- Experimenting with different deep learning network architectures for improving accuracy of detection, depth estimation and classification while keeping computation power required reasonably low.
- Developing a data efficient training pipeline by using synthetic data.
- Experimenting with techniques to quickly and efficiently adapt/tune deep learning networks for different geographies and weather conditions.
- Developing techniques to detect rare road objects.
- Improving KPIs for computer vision deep learning networks.
- Be involved in publishing papers and patents relating to innovations in perception.
- MS/BS degree in CS/EE/ECE/Computer vision or equivalent industry experience.
- 1-2 years of experience in computer vision.
- 1-2 years of experience in deep learning application to computer vision - object detection, image classification and image segmentation.
- Experience with Deep Learning frameworks like Tensorflow, PyTorch.
- Programming experience in C++ and Python.
- Experience in machine learning on embedded systems
- Experience in applying OpenCV