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Skydio

Autonomy Engineer Intern - Computer Vision/Deep Learning Summer 2027

San Mateo, California, United States (Remote)interninternAdded today

About this role

Join Skydio's autonomy team as a Computer Vision/Deep Learning intern to develop and research the algorithms that enable autonomous drone flight. You'll work alongside experienced researchers to prototype novel approaches, implement features, and advance the state-of-the-art in aerial intelligence systems.

What you'll do

  • Design and implement computer vision and deep learning algorithms for autonomous drone systems
  • Research and prototype new approaches to advance autonomy capabilities
  • Take direct ownership of a meaningful project that impacts product development
  • Characterize and quantify performance of software and hardware components
  • Develop new features that enhance autonomous flight and user experience
  • Collaborate with core software development team on algorithm evaluation and deployment

What they're looking for

  • C++ and/or Python programming
  • PyTorch deep learning framework
  • Computer vision algorithms and techniques
  • Deep learning and neural networks
  • Software engineering and code architecture
  • Motion planning or dynamics and controls (preferred)
  • 3D graphics or distributed systems (preferred)
  • Mathematical foundations and algorithm analysis

Benefits

  • Work on cutting-edge autonomous systems deployed in real products
  • Mentorship from world-class researchers and engineers
  • Opportunity to push state-of-the-art in drone autonomy
  • Fast-paced, collaborative team environment
  • Eligible for benefit plans and various incentives
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Skydio

Skydio builds autonomous drone technology powered by sophisticated RF, electrical, and embedded systems. The company is hiring RF engineers, electrical engineers, embedded software engineers, cloud platform engineers, and deployment engineers to develop and support its connected drone products.

Website
skydio.com
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Likely interview questions

  • Tell us about a computer vision or deep learning project where you solved a challenging problem—what was your approach and what did you learn?
  • How have you used PyTorch in a project, and what motivated your choice of that framework?