About the role:

Learning a semantic and geometric understanding of the world from visual data is the core of our company. We are pushing the boundaries of what is possible with deep networks in enabling intelligent, flying robots to plan, gather and analyze visual information from the diverse environments they are operating in to solve critical problems. If you are excited about solving real world problems in scene understanding including multimodal learning, using vision-language models for improved scene understanding and generative models for text-to-image or image-to-image tasks, while leveraging massive amounts of structured video data, we would love to hear from you.

How you’ll make an impact:

• Leverage breakthrough progress in multimodal AI to build total scene understanding for the most advanced productized robots in the world.
• Design and implement deep learning solutions that solve real world problems such as multimodal search/retrieval/captioning/visual question answering for large image/video libraries, text-to-image modeling for generative applications, zero-shot and few shot detection/classification/segmentation, outlier detection
• Design, adapt, optimize and fine-tune deep networks using large language-image model backbones for real world use cases
• Design data engineering, prompt engineering and de-biasing methods for robust model performance
• Refine and optimize models for low-latency on embedded hardware and cloud
• Characterize and quantify the performance of the DL systems
• Research and prototype new approaches
• Be a generalist helping out on all aspects of the software when needed

What makes you a good fit:

• Demonstrated hands-on experience training and deploying deep learning models for computer vision or multimodal learning
• Experience with data engineering and ML Operations for reliable deployment of DL models
• Solid software engineering foundation and commitment to writing clean, well-architected code (in Python or C++, preferably both)
• Real experience prototyping, training, optimizing, and deploying deep neural networks
• Ability to read and contextualize scientific papers and literature in computer vision
• Ability to thrive in a fast paced, collaborative, small team environment

Experience:

• Master’s or Ph.D. in Electrical Engineering, Computer Science or related discipline
  
  

Compensation Range:

• The annual base salary range for this position is $190,000 - 245,000*.  Compensation will vary based on factors, including skill level, proficiencies, transferable knowledge, and experience. In addition to base salary, Skydio full-time employees are eligible to enroll in our benefit plans and take advantage of a variety of incentives and stipends.

          *For some positions the pay may be dependent upon the individual’s regional location.

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