Job description

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. Job Summary: The Engineering Manager, State Estimation will lead a high-performing team focused on developing advanced mapping, localization, and SLAM (Simultaneous Localization and Mapping) solutions for embedded camera systems. You will oversee the research, development, and deployment of large-scale mapping and localization solutions, while shaping the technical roadmap and ensuring successful collaboration across device, cloud, and applied AI teams. Responsibilities: - Build, mentor, and manage a team of engineers developing state-of-the-art mapping, localization, and SLAM algorithms. - Set technical direction and project priorities, aligning them with broader organizational goals. - Drive high-impact, cross-functional projects from conception through deployment, coordinating with research, hardware, and product teams. - Provide technical guidance on algorithm design, system architecture, and implementation, while ensuring best practices in software development and performance optimization. - Foster a culture of innovation, technical rigor, and collaboration across the team. - Develop and maintain project roadmaps, milestones, and technical documentation. - Partner with senior leadership to define long-term strategies for localization, state estimation, and multi-sensor calibration. - Review and approve designs, architectures, and implementations, ensuring technical excellence and scalability. - Lead recruitment, hiring, and performance management to grow a world-class engineering team. REQUIRED QUALIFICATIONS: - Bachelor of Science degree (M.S. or Ph.D. preferred) in Electrical and Computer Engineering, Robotics, Machine Learning, Computer Science, or a related field. - 10+ years of industry experience (8+ years with an M.S., 6+ years with a Ph.D.), including significant leadership or management responsibilities. - Proven experience leading engineering teams working on state estimation, localization, or SLAM technologies. - Strong foundation in C++ development, geometric computer vision, stochastic processes, and nonlinear/convex optimization. - Deep understanding of filtering algorithms (e.g., Kalman, particle filters) and optimization-based methods (e.g., nonlinear least squares). - Familiarity with camera geometry, structure from motion, multi-sensor fusion, factor graphs, and related state estimation concepts. - Strong track record of technical execution combined with leadership and team-building skills. - Exceptional communication skills, with the ability to collaborate effectively across engineering, research, and product functions. - Experience in technology transfer and delivering research innovations into production systems. PREFERRED QUALIFICATIONS: - Demonstrated success deploying SLAM/VIO estimators in real-world applications. - Experience with multi-sensor systems, including GPS, IMU, camera, and wheel odometry. - Exposure to integrating deep learning with classical state estimation approaches. - Strong record of published research or contributions to the robotics and computer vision community. - Experience scaling and leading multi-disciplinary engineering teams

Requirements

Must-haves

Build, mentor, and manage a team of engineers developing state-of-the-art mapping, localization, and SLAM algorithms.
Set technical direction and project priorities, aligning them with broader organizational goals.
Drive high-impact, cross-functional projects from conception through deployment, coordinating with research, hardware, and product teams.
Provide technical guidance on algorithm design, system architecture, and implementation, while ensuring best practices in software development and performance optimization.
Foster a culture of innovation, technical rigor, and collaboration across the team.
Develop and maintain project roadmaps, milestones, and technical documentation.
Partner with senior leadership to define long-term strategies for localization, state estimation, and multi-sensor calibration.
Review and approve designs, architectures, and implementations, ensuring technical excellence and scalability.
Lead recruitment, hiring, and performance management to grow a world-class engineering team.
10+ years of industry experience (8+ years with an M.S., 6+ years with a Ph.D.), including significant leadership or management responsibilities.
Proven experience leading engineering teams working on state estimation, localization, or SLAM technologies.
Strong foundation in C++ development, geometric computer vision, stochastic processes, and nonlinear/convex optimization.
Deep understanding of filtering algorithms (e.g., Kalman, particle filters) and optimization-based methods (e.g., nonlinear least squares).
Familiarity with camera geometry, structure from motion, multi-sensor fusion, factor graphs, and related state estimation concepts.
Strong track record of technical execution combined with leadership and team-building skills.
Exceptional communication skills, with the ability to collaborate effectively across engineering, research, and product functions.
Experience in technology transfer and delivering research innovations into production systems.

Nice-to-haves

Bachelor of Science degree (M.S. or Ph.D. preferred) in Electrical and Computer Engineering, Robotics, Machine Learning, Computer Science, or a related field.
Demonstrated success deploying SLAM/VIO estimators in real-world applications.
Experience with multi-sensor systems, including GPS, IMU, camera, and wheel odometry.
Exposure to integrating deep learning with classical state estimation approaches.
Strong record of published research or contributions to the robotics and computer vision community.
Experience scaling and leading multi-disciplinary engineering teams

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Keywords to mirror

aimachine learning

Platform: ashby
Effort: quick

Benefits

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Vision