About the job
Skydio stands at the forefront of autonomous flight technology, redefining the future of drones and aerial mobility. As the leading US drone manufacturer, our team blends unrivaled expertise in artificial intelligence with top-tier hardware and software development, operational excellence, and a commitment to customer satisfaction. We empower a diverse range of drone users, from utility inspectors and first responders to military personnel on the battlefield and beyond.
About the Role:
At Skydio, our autonomy system relies on advanced semantic and geometric comprehension of the world through visual data. We are pushing the limits of real-time deep learning networks to enhance intelligent mobile robotics. If you are passionate about utilizing vast structured video datasets to tackle challenges in Computer Vision (CV), including object detection, tracking, optical flow estimation, and segmentation, we want to connect with you.
As a Deep Learning Infrastructure Engineer, you will play a pivotal role in constructing and scaling the infrastructure that underpins Skydio’s Deep Learning (DL) and AI initiatives. Collaborating closely with our autonomy, embedded, and cloud teams, you will deliver innovative capabilities and support the deep learning team.
Your Impact:
Develop high-performance solutions for deep learning inference tailored to CV workloads, ensuring high throughput and low latency across various hardware platforms.
Analyze the performance of CV and Vision Language Models (VLMs) to pinpoint bottlenecks and opportunities for optimization and enhanced power efficiency.
Design and implement comprehensive MLOps workflows for model deployment, monitoring, and retraining processes.
Apply your advanced machine learning knowledge to improve system performance through training or runtime frameworks and model efficiency tools.
Innovate new methods to enhance training efficiency.
Develop GPU kernels for custom architectures and optimized inference.
Create SDKs that facilitate customer and external developer engagement in building autonomous workflows utilizing Machine Learning (ML).
Utilize your expertise and adherence to best practices to uphold and enhance Skydio’s engineering standards.
Qualifications:
Hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment.
Proficiency in deep learning frameworks and tools.
Strong understanding of computer vision principles and practices.
Excellent problem-solving skills and attention to detail.

