Senior Algorithm Engineer Sydney

Advanced Navigation is a global leader in navigation and autonomous systems. By leveraging capabilities in software-enhanced hardware, every solution delivers unrivaled capabilities and exceptional performance across land, air, sea and space applications where GPS is unreliable.

Made possible with extensive research, testing and vertically integrated manufacturing, the company has progressed into deep technology fields, including robotics, inertial, photonic and quantum sensing, artificial intelligence, underwater acoustics, and GPS antennas and receivers. Customers choose Advanced Navigation for rapid product delivery and unmatched technical field expertise.

Headquartered in Sydney, Australia, with research and production facilities nationwide and offices globally. Advanced Navigation is an Australian manufacturer exporting worldwide. #JoinTheAutonomyRevolution

About the role

Advanced Navigation has a heavy engineering focus, with R&D capability in Sydney, Canberra, Newcastle and Perth. Our products are developed and manufactured in Australia and are designed to deliver critical navigation information across sea, land and air platforms including surface, subsea assets, ground vehicles, and unmanned aerial vehicle applications.

We are seeking a highly skilled Senior Algorithm Engineer with a passion for robotics, and sensor fusion , to research, develop, and implement advanced state estimation algorithms for our navigation systems. The ideal candidate will have a strong theoretical foundation and practical experience in solving complex real-world problems, with a focus on Kalman filtering and related techniques.

What you'll do

- Invent and develop new ideas into commercially viable innovations.
- Design, develop, and implement advanced sensor-fusion navigation algorithms, with a focus on state estimation techniques (e.g., Kalman filters)
- Model and simulate algorithms in MATLAB to optimize navigation performance across various sensors, vehicles, and customer use cases.
- Collaborate with embedded engineers to implement, test, and validate algorithms on resource-constrained devices.
- Analyze and interpret performance data to improve algorithm accuracy and robustness.
- Stay up-to-date with the latest research and advancements in state estimation, sensor fusion, and related fields.
- Contribute to the development of modular, readable, and well-documented code.
- Participate in code reviews and contribute to improving software engineering best practices.
- Troubleshoot and resolve complex algorithm-related issues.

Qualifications

- Deep understanding of the fundamentals of state estimation techniques, including Kalman filtering (KF), Extended Kalman filtering (EKF), and Unscented Kalman filtering (UKF).
- Proven experience in developing and testing novel algorithms to solve real-world problems.
- High-level proficiency in MATLAB for algorithm modeling and simulation.
- Strong mathematical skills, including linear algebra, probability theory, and statistics.
- Proficiency in version control systems, particularly Git.
- Ability to write modular, readable, and maintainable code.
- Experience with Bayesian inference, object tracking, target tracking, or SLAM (Simultaneous Localization and Mapping) is desirable
- Excellent research literacy, with the ability to comprehend and apply the latest research papers.
- Experience in implementing algorithms intended for resource-constrained embedded systems.
- Experience with MEX for MATLAB.
- Knowledge of digital signal processing (DSP)
- First-class honours degree in a relevant field such as Engineering, Robotics, Mathematics, Physics, or Computer Science.

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