About the job
About Us
At Hayden AI, our goal is to leverage computer vision technology to revolutionize how transit systems and government agencies tackle real-world challenges.
Our cutting-edge mobile perception systems facilitate bus lane enforcement, transportation optimization, and more, enabling clients to enhance transit efficiency, improve street safety, and promote sustainable practices.
About the Perception Team
The Perception Team at Hayden AI specializes in developing and refining AI algorithms that drive our mobile enforcement systems, analyzing video and image data to identify traffic violations, parking infractions, and other urban compliance issues. This collaborative team works closely with both cloud and device engineering to create and implement perception pipelines that provide actionable insights for our clients.
About the Role
As a Software Engineering Intern focusing on Perception at Hayden AI, you will be integral to the development of AI systems that support our mobile enforcement platform. You will engage with computer vision and machine learning models to process real-world video and image data for detecting traffic violations and urban compliance events.
This position intersects machine learning, data analytics, and real-world deployment. Your responsibilities may include improving model accuracy, refining training datasets, assessing edge cases, optimizing inference performance, and developing tools to enhance perception pipelines across cloud and on-device environments.
This is not a role for side projects; you will take ownership of significant technical work that impacts our production systems. Under the mentorship of a senior engineer, you will design experiments, implement enhancements, evaluate performance, and help deliver improvements that influence how our systems interpret and respond to the physical world.
This internship is perfect for individuals passionate about applied AI, particularly in computer vision, model evaluation, and deploying machine learning systems in real-world settings.
The position is based in San Francisco, with a hybrid work schedule requiring at least three days in the office each week.

