Autonomy Engineer - Deep Learning

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders , soldiers in battlefield scenarios , and beyond .

About the role:

Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent aerial robots that can autonomously navigate in unknown environments and deliver operational value to users. If you are excited about real world applications of deep learning and solving difficult problems in computer vision and autonomy, we would love to hear from you.

As a Deep Learning Engineer, you will be responsible for training and deploying optimized models to our products for solving challenging problems such as optical flow estimation, stereo depth estimation, object detection, segmentation and tracking, visual place recognition, localization and mapping, few-shot learning, occupancy networks, automated path planning etc.

How you'll make an impact:

• Design, implement, and deploy computer vision and multimodal deep learning models for Skydio’s autonomy system

• Leverage massive amounts of real world video and other sensor data for data mining, curation, labeling, training and evaluation

• Leverage large scale and diverse synthetic data to power deep learning algorithms

• Leverage state-of-the-art foundation models for knowledge distillation and label efficient learning

• Refine and optimize models for low-latency on embedded hardware

• Develop evaluation benchmarks and metrics to quantify the performance of autonomous systems

• Be a generalist helping out on all aspects of the software when needed

What makes you a good fit:

• M.S. or Ph.D. in computer science, electrical engineering or related discipline

• Demonstrated hands-on experience designing, training and deploying deep learning models

• Ability to deliver high quality, well-architected code (Python/PyTorch and preferably, C++)

• Leverage state-of-the-art academic papers and literature for fast iteration

• Ability to thrive in a fast paced, collaborative and highly technical team environment

• Comfortable navigating and delivering within a complex codebase

• Strong communication skills

• Obtaining FAA Part 107 certification within the first 60 days of employment is strongly encouraged for all Skydio employees and required for certain positions.

Compensation: At Skydio, our compensation packages for regular, full-time employees include competitive base salaries, equity in the form of stock options, and comprehensive benefits packages. Compensation will vary based on factors, including skill level, proficiencies, transferable knowledge, and experience. Relocation assistance may also be provided for eligible roles. The annual base salary range for this position is $170,000 - $277,500*. Fundamentally, we believe that equity is the key to long-term financial growth, and we ensure all regular, full-time employees have the opportunity to significantly benefit from the company's success. Regular, full-time employees are eligible to enroll in the Company’s group health insurance plans. Regular, full-time employees are eligible to receive the following benefits: Paid vacation time, sick leave, holiday pay and 401K savings plan. This position and all associated benefits are subject to applicable federal, state, and local laws, as well as the Company’s policies and eligibility criteria.

*Compensation for certain positions may vary based on the position's location.

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At Skydio we believe that diversity drives innovation. We have created a multidisciplinary environment that embraces the power of diverse perspectives to create elegant solutions for complex problems. We are committed to growing our network of people, programs, and resources to nurture an inclusive culture.