Posting record
Open 11+ days
- Haydenai's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Haydenai, so its true age is longer.
Last checked Nov 1, 2026.
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Upload your resumeWhat it asks of you
- 10+ years of experience
What the posting discloses
- Pay
- $240k to $310k a year USD
Not stated: Real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
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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