About the job
Skydio stands as the premier drone company in the United States and a global leader in autonomous flight technology, which is pivotal for the future of drones and aerial mobility. Our team merges profound expertise in artificial intelligence with exceptional hardware and software product development, operational excellence, and an unwavering commitment to customer satisfaction. We empower a diverse range of drone users, from utility inspectors to first responders, and military personnel in various scenarios.
About the Role:
At the heart of our autonomy system is the ability to learn a semantic and geometric understanding of the world through visual data. We are at the forefront of pushing the limits of real-time deep networks, driving advancements in intelligent mobile robotics.
If you are passionate about tackling open-ended challenges in object detection and tracking, motion prediction, flow estimation, and comprehensive scene understanding, while utilizing extensive structured video data, we encourage you to apply.
Your Impact:
Develop and deploy deep learning solutions to address detection, tracking, segmentation, and optical flow estimation tasks in real-time on Skydio drones.
Utilize cutting-edge methods in unsupervised learning, few-shot learning, and foundational models to enhance data-efficient machine learning.
Curate and augment synthetic data that fuels our deep learning algorithms in conjunction with vast amounts of structured video data.
Refine and optimize models for low-latency performance on embedded hardware.
Evaluate and quantify the performance of vision systems.
Engage in research and prototype innovative approaches.
Act as a versatile contributor across various software domains as needed.
Your Qualifications:
Proven hands-on experience in creating and deploying deep learning models.
Experience in curating both synthetic and real-world image datasets.
Strong software engineering background with a dedication to writing clean, well-architected code (proficiency in Python or C++, ideally both).
Demonstrated experience in prototyping, training, optimizing, and deploying deep neural networks.
Ability to read and contextualize scientific research and literature in computer vision.
Capacity to thrive in a fast-paced, collaborative small team environment.

