Hayden AI
Senior State Estimation Engineer
460 Bryant St, San Francisco, CA 94107-2594
Hybrid · Full-time · $200k–$261k (as posted)
First seen by offpeak October 4, 2026
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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.
What the job involves
As a Senior State Estimation Engineer at Hayden AI, you will be asked to derive and implement novel real-time pose estimation algorithms. Research, develop and implement algorithms to solve large-scale mapping. Collaborate with other engineers to develop algorithms for in-situ and in-factory multi-sensor calibration.
Responsibilities
Contribute to high impact, multidisciplinary projects across teams
Program and develop software in C++ and/or python
Derive and implement novel, real-time pose estimation algorithms
Research, develop and implement algorithms to solve problems such as large-scale mapping, probabilistic object tracking, online/offline sensor calibration and/or vision-based localization
Collaborate with deep learning, device, and cloud teams to improve overall system architectures
Provide mentorship to our junior engineers
Required Qualifications
Master of Science degree or the foreign equivalent in Electrical and Computer Engineering, Robotics, Machine Learning, Computer Science, Electrical Engineering or a related field.
Five (5)+ years of experience in the position offered, as a software engineer, software engineer intern, or a related state estimation engineer role.
Five (5) years of experience with all of the following: programming in C++; designing and developing software; classical ML, Linear Algebra,
Stochastic Processes, Geometric Computer Vision and Optimization (Convex, Nonlinear); Kalman Filter, MAP, Sequential Monte Carlo (particle
filter), Nonlinear Least squares, IRLS and MHT; GPS, IMU, camera and wheel odometry.Experience deploying SLAM/VIO estimators in a real-world application.
Work with multiple sensors such as GPS, IMU, camera, LIDAR, and wheel odometry.