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Pedestrian Dead Reckoning (PDR) System Engineer

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Waymap is the world’s leading navigation company for the visually impaired, revolutionizing indoor and outdoor navigation through cutting-edge sensor fusion, AI, and deep-tech solutions. Our smartphone-based navigation system enables seamless, GPS-free positioning, empowering greater independence and accessibility for users worldwide.

As we scale rapidly to meet growing demand, we are seeking a Pedestrian Dead Reckoning (PDR) System Engineer to improve the accuracy and robustness of our MATLAB-based PDR and map-matching systems. You will also contribute to forward-looking innovations, helping shape the future of Waymap’s navigation technology.

Role

As a PDR System Engineer, you will be part of our cutting-edge R&D team, refining and optimizing pedestrian motion models, map matching, and sensor fusion algorithms. Your work will directly impact the precision and reliability of our navigation systems across indoor and outdoor environments.

This is a high-impact, problem-solving role ideal for someone with experience in MATLAB, navigation systems, sensor fusion, and motion modelling, who is also eager to explore emerging localization technologies (for example based on computer vision/SLAM).

Even if you don’t meet all the specific criteria listed below, we’d still love to hear from you if you can draw on similar experience in a closely related area!

Key Responsibilities

  • Enhance pedestrian dead reckoning (PDR) algorithms for indoor and outdoor navigation.
  • Improve sensor fusion techniques, integrating IMU (accelerometer, gyroscope, magnetometer, barometer), GPS, and other data sources.
  • Develop and refine map matching algorithms to align PDR trajectories with real-world maps.
  • Optimize motion modelling, step detection, and stride estimation for more accurate pedestrian tracking.
  • Work with Android and iOS development teams to integrate real-time PDR and map-matching enhancements into mobile applications.
  • Debug, test, and refine algorithms to ensure scalability, robustness, and accuracy.
  • Forward-looking R&D: Research and prototype next-generation localization technologies, such as AI-driven positioning, ultra-wideband (UWB), and computer vision-based mapping.
  • Stay updated on emerging sensor-based navigation and localization technologies.

Requirements

Must-Have:

✔ Strong experience in MATLAB or other programming languages, algorithm development, prototyping, and data analysis.

✔ An ability to write performant and efficient code
✔ Understanding of pedestrian dead reckoning (PDR), motion modelling, and sensor fusion.
✔ Experience working with inertial data and other sensor-based navigation techniques.
✔ Familiarity with map matching techniques (e.g., probabilistic methods, Hidden Markov Models, particle filters, graph-based approaches).
✔ Strong problem-solving skills, with the ability to analyse and optimize algorithms.
✔ STEM background (degree in Computer Science, Robotics, Electrical Engineering, Mathematics, or a related field).

Nice-to-Have:

➕ PhD degree with applied research background

➕ Experience in C for algorithm optimization and mobile application integration.
➕ Knowledge of SLAM (Simultaneous Localization and Mapping) or other sensor-based localization techniques.
➕ Familiarity with vision-based localization or radio based positioning techniques (BLE, UWB, etc.).
➕ Experience with AI/ML for improving localization accuracy.

Benefits & Perks

🌍 Remote-first with occasional travel to London office
📈 Work on world-changing technology with a real-world impact
💡 Collaborate with top-tier engineers, developers, and navigation experts
🚀 Fast-growing deep-tech start-up

🔗 Apply Now – Send your CV and a short cover letter explaining why you’re a great fit for this role.

Contract Type: FULL_TIME

Specialism: Technology & Digital

Focus: Infrastructure

Industry: IT

Salary: Negotiable

Workplace Type: Remote

Experience Level: Associate

Location: Cape Town

Job Reference: Y5BZ36-3FB23129

Date posted: 26 May 2025

Consultant: Eloise Ladouceur