
At Hayden AI, we’re pioneering real world problem solving powered by AI and machine learning. From bus lane and bus stop enforcement to digital twin modeling and more, our clients use our mobile perception system to speed up transit, make streets safer, and create a more sustainable future. Our privacy first approach ensures that our technologies comply with security and privacy regulations and protect personal information while fostering innovation.

At Hayden AI, we’re pioneering real world problem solving powered by AI and machine learning. From bus lane and bus stop enforcement to digital twin modeling and more, our clients use our mobile perception system to speed up transit, make streets safer, and create a more sustainable future. Our privacy first approach ensures that our technologies comply with security and privacy regulations and protect personal information while fostering innovation.
Headquarters / Founded: San Francisco; founded 2019
Core product: Vehicle-mounted vision AI and edge spatial analytics for transit zone enforcement and digital twin modeling
Security certifications: SOC 2 Type II and ISO/IEC 27001
Recent financing: Series C led by The Rise Fund (TPG) announced July 2024
Reported employees: Approx. 185
| Company |
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Urban mobility, transit enforcement, street safety, and spatial analytics for cities.
2019
Software Development
$20M
Series A participation included Autotech Ventures, BootstrapLabs, Modern Venture Partners
$53M
Described as oversubscribed
$90M
Announced as growth equity financing
About Us At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
What the job involves
As an Engineering Manager, you will lead the development and refinement of a cutting-edge perception system, leveraging deep learning for real-world applications. Your expertise in computer vision, deep learning, and team leadership will drive performance improvements and seamless integration across the company.
Responsibilities
Qualifications
Ph.D. or Master's in Robotics, Machine Learning, Computer Science, Electrical Engineering, or a related field.
2+ years leading and managing teams focused on developing real-world computer vision and perception systems using deep learning on edge devices.
Proven ability to deploy these systems with:
Deep Learning Frameworks: Expertise in PyTorch or TensorFlow (one mandatory, familiarity with both a plus).
Computer Vision Libraries: OpenCV.
Deployment Optimization Tools: TensorRT.
Strong Python programming and software design with experience in Pandas.
Experience deploying DL models to run on real-world, resource-constrained, systems with a pragmatic approach towards problem-solving.
Demonstrated proficiency in data science and traditional machine learning (SVMs, Random Forests). Prior experience with automated machine learning pipelines is desirable.
Proven industry track record with experience in:
Automated data annotation for computer vision.
Training multi-task and semi-supervised deep learning models for video data.
Familiarity with designing multi-modal deep learning models incorporating temporal context and geometrical constraints is a plus.