Staff Deep Learning Engineer, Perception

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 realworld 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 cuttingedge perception system, leveraging deep learning for realworld 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 crossfunctional teams.

• Actively contribute to the development and refinement of the perception system in a handson 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 realtime analysis.

• Collaborate with crossfunctional teams (clouddevice) 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 decisionmaking.

• Required Qualifications:

  • Ph.D. or Masters 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 customerfacing 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 realworld, resourceconstrained systems with a pragmatic approach towards problemsolving.

  • 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 multitask and semisupervised deep learning models for video data.

  • Familiarity with designing multimodal deep learning models that incorporate temporal context and geometrical constraints is a plus.

  • Crossfunctional knowledge of cloud and device systems for deployment