Engineering Manager, State Estimation

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