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.
Job Summary:
As the Staff Deep Learning Engineer, you will play a critical role in 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. You will define and lead projects, and find new areas to make an impact and improvements at Hayden AI.
Responsibilities:
Define and lead projects, driving the entire perception system development life cycle from problem definition to deployment and ongoing improvement.
Lead and mentor cross-functional teams.
Actively contribute to the development and refinement of the perception system in a hands-on manner.
Develop robust computer vision algorithms for object detection, tracking, semantic segmentation, and classification.
Design and train deep learning models for complex urban scene perception and real-time analysis.
Collaborate with cross-functional teams (cloud/device) for seamless integration and monitoring of perception models.
Analyze data to identify performance bottlenecks and opportunities for enhancing the perception system.
Automate the improvement cycles of deep learning models used within the perception system.
Communicate technical findings and insights effectively to stakeholders across the company to drive performance improvements.
Utilize data visualization tools to present complex information clearly for informed decision-making.
Required Qualifications:
Ph.D. or Master's in Robotics, Machine Learning, Computer Science, Electrical Engineering, or a related field.
10+ years of relevant experience in machine learning, deep learning and computer vision (object tracking, semantic segmentation, urban scene understanding).
Proven ability to deploy deep learning systems in real customer-facing production environments.
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 multimodal deep learning models that incorporate temporal context and geometrical constraints is a plus.
Cross-functional knowledge of cloud and device systems for deployment
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What We Do
Artificial intelligence is already impacting almost every aspect of our lives. But cities still rely on outdated technologies that are too expensive to scale and unable to deliver on their promise. As a result, streets are becoming unsafe, and cities are becoming unmanageable. Hayden AI was founded on the belief that by combining mobile sensors with artificial intelligence, we can help governments bridge the innovation gap while making traffic flow less dangerous and more efficient. Led by a team of experts in machine learning, data science, transportation, and government technology, we’ve developed the world’s first autonomous traffic management platform — simultaneously serving citizens and multi-agency missions to help cities become safer and more sustainable.
