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Salary
$240k – $310k per year
Location
Hybrid (San Francisco, United States)
Seniority
Staff · 10+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Jun 29, 2026. Hayden AI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Hayden AI is an American artificial intelligence technology company specializing in smart city solutions and automated traffic enforcement. Founded in 2019, the company utilizes mobile computer vision and edge processing systems—often mounted on public transit buses—to detect parking and traffic violations in real time. By automating enforcement in bus lanes and stop zones, it helps municipalities improve urban transit efficiency, enhance pedestrian safety, and reduce city traffic congestion.

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

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