Deep Learning Research Engineer
Santa Monica, CA, US
Advanced Engineering – Autonomous Vehicle Technology (R&D)
nuTonomy aims to be the first company in the world to launch an autonomous taxi system, and we are building up an awesome team to make this goal a reality. We are developing the first-of-its-kind complete solution for providing point-to-point mobility via large fleets of autonomous vehicles. This includes software for autonomous vehicles, smartphone-based ride hailing, fleet management, and teleoperation. The company's software has been tested extensively on public roads in the U.S. and Singapore. We offer a unique opportunity to work closely with experts from a wide array of backgrounds, to create ground-breaking technology with potential for huge impact. As a member of a fast-growing start-up, you will be able to make a large contribution to the final product. For more information about nuTonomy, visit: www.nutonomy.com
We are looking for a Deep Learning Research Engineer that will focus on architecting, training and analyzing deep neural networks to extract rich semantic information from multiple sensor modalities, with the goal of using the learned models in real-time for a variety of tasks, including object detection, scene segmentation, tracking & fusion, sensorimotor learning for calibration and fault detection, and behavior prediction. We are looking for experts with either (or both) academic or industry backgrounds.
In this role you would work closely with other researchers & engineers to build a fully-integrated autonomous driving stack. nuTonomy’s goal is to create provably safe and efficient vehicles, so we particularly value a rigorous statistical background and expertise regarding providing rigorous performance bounds.
To support your work, you will be able to use a state-of-the-art scalable computing, simulation, and testing environment, as well as a vast database of well annotated data from nuTonomy’s fleet of autonomous vehicles. You will work together with an awesome group of motivated colleagues, both industry professionals as well as leading researchers from academia, who like to approach problems with both creativity and rigor, to push beyond the state of the art.
- Design deep neural networks for the autonomous vehicle stack.
- Develop training and testing pipelines.
- Work with customers to define performances metrics and goals.
- Manage data mining & annotation.
- Ms. in Machine Learning, Applied Mathematics, Statistics, Computer Science or related field.
- Experience of architecting, training and analyzing CNNs for at least one of the following applications: Object detection, Image segmentation, Sensor fusion, Temporal fusion (tracking)
- Experience with PyTorch or other deep learning frameworks.
- Excellent analytical, communication, and writing skills.
- Experience developing software as part of a team.
- Fluency in Python.
- Ph.D in computer science or similar field.
- Software development experience from industry.
- Experience in automotive or other real-time and embedded systems.
- GPU/CUDA programming skills.
- Proven track record of publications in relevant conferences (CVPR, ICML, NIPS, ICCV, ICLR…)
- Familiarity with C++, CUDA, Git, CMake, continuous integration tools and the agile development process.
Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.