S
Skydio
Autonomy Engineer (Deep Learning)
Skills
Deep LearningData MiningPythonPyTorch
2 months ago
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Important information
Contract type:
Permanent
Salary:
$170,000 – $277,500 / year
Location:
United States
Work mode:
Onsite
Published on:
29 August 2026
What they need
- 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
- 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
- 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- Strong communication skills
- Leverage state-of-the-art academic papers and literature for fast iteration
- Ability to deliver high quality, well-architected code (Python/PyTorch and preferably, C++)
- Ability to thrive in a fast paced, collaborative and highly technical team environment
- Comfortable navigating and delivering within a complex codebase
- Demonstrated hands-on experience designing, training and deploying deep learning models
- M.S. or Ph.D. in computer science, electrical engineering or related discipline
- 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
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