Is making vehicles fly on their own your passion? Are you looking for a role that will allow you to sculpt the control programs for the first generation of flying cars ? If you answered “Yes” then this is “The” role for you.
As a Senior Deep Learning Engineer, you will report directly to the Director of Engineering. You will be responsible for the development of vision-based deep learning algorithms that enable autonomous aircraft to analyze, understand, and interact with their environment safely. These perception algorithms are critical to enabling our aircraft to fly without pilots.
Specifically, your responsibilities will include:
- Designing, training, and tuning state-of-the-art vision-based deep learning algorithms to perceive the environment around autonomous aircraft on the ground and in the air;
- Driving the efficient implementation of these algorithms for deployment to onboard computer systems;
- Supporting the data flows that enable the development and testing of deep learning algorithms;
- Interfacing with external companies for tasks that support model development (ie. annotation, simulation, etc.);
- Communicating methods and results effectively to the rest of our team.
- Advanced degree in computer science, robotics, electrical engineering, applied mathematics, computational neuroscience, or a related field and at least two years of professional experience related to computer vision applications.
- Strong theoretical and applied knowledge of neural network architectures and computer vision algorithms for scene understanding including object detection, classification, segmentation, depth and motion estimation;
- Experience developing novel deep learning models with TensorFlow, PyTorch, Caffe, or another common framework;
- Expertise in Python, Java, or C++;
- Demonstrated ability to maintain currency with the latest developments in your field;
- Personal drive and intellectual curiosity to do what hasn’t been done before, coupled with an appreciation for overcoming challenges.
Strong preference will be given to candidates with:
- Real-world experience with mobile autonomous systems such as robots, cars, and UAVs;
- Familiarity with sensors including cameras, radar, and lidar;
- Expertise in developing for GPU computation;
- Experience optimizing trained deep learning models for deployment;
- Software development experience in a production environment.