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Senior Algorithm Engineer (GNSS)

Posted 2 Days Ago
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In-Office
Sydney, New South Wales, AUS
Senior level
In-Office
Sydney, New South Wales, AUS
Senior level
The Senior Algorithm Engineer (GNSS) will design, prototype, and tune GNSS algorithms, lead sensor fusion efforts, evaluate hardware, and provide technical mentorship while ensuring mathematical integrity in navigation products.
The summary above was generated by AI

Advanced Navigation is the world’s most determined innovator in AI robotics and navigation technologies across land, air, sea and space applications. Founded on a culture of research and discovery, Advanced Navigation's mission is to be the catalyst of the autonomy revolution. Fields of expertise include artificial intelligence, underwater sonar, GNSS, radio frequency systems, inertial sensors, robotics, quantum sensors and photonics. 

Today, Advanced Navigation is a supplier to some of the world's largest companies, including Airbus, Boeing, Google, Tesla, NASA, Apple, and General Motors. Discover it for yourself: https://youtu.be/F7uAqs1gtuk


Overview of the role

As Advanced Navigation enters a new phase of growth, the Data Fusion team is seeking a Senior Algorithm Engineer (GNSS) to serve as the internal Subject Matter Expert (SME) for satellite navigation. While our team has deep expertise in Inertial Navigation (INS), you will be the bridge that integrates raw GNSS observables into our world-class fusion engine.

You will own the mathematical integrity of our GNSS solutions, from evaluating high-end receiver hardware and CRPA antennas to designing tightly coupled architectures that remain resilient against spoofing and high-multipath environments. This is a high-impact, individual contributor role where your prototypes will define the next generation of resilient PNT (Position, Navigation, and Timing) products.

What you will do 

  • Algorithm R&D: Design, prototype, and tune multi-constellation, multi-frequency GNSS fusion algorithms (RTK/PPP) using MATLAB.
  • Sensor Fusion: Lead the development of tightly coupled GNSS/INS architectures, ensuring optimal state estimation using EKF, UKF, and Least-Squares Optimization.
  • Hardware Evaluation: Act as the technical authority for selecting and characterising third-party GNSS hardware, including receivers and CRPA (Controlled Reception Pattern Antennas).
  • Integrity & Security: Design and implement detection and mitigation strategies for GNSS interference and spoofing.
  • Field to Lab: Lead the analysis of real-world data from field tests to characterize sensor error models and refine filter performance.
  • Cross-Functional Collaboration: Partner with Embedded Engineers to oversee the successful translation of your mathematical models into real-time C++ implementations.
  • Technical Mentorship: Act as the primary GNSS resource for the wider product organisation, providing guidance on satellite geometry, signal processing, and error budgets.


What we expect

  • Degree qualified (Master’s or PhD preferred) in Aerospace, Geodesy, Mechatronics, Electrical Engineering, or a related field with a focus on Estimation Theory.
  • A "Practical Scientist" mindset: Comfortable deriving filters from first principles but focused on what works in the "noisy" real world.
  • 5+ years of experience in navigation algorithm development.
  • Proven track record with tightly coupled integration (fusing GNSS pseudorange, carrier phase, and Doppler directly with IMU data).
  • Deep proficiency in MATLAB and for high-fidelity simulation and data analysis.
  • Hands-on experience with GNSS hardware (u-blox, NovAtel, Septentrio, etc.) and understanding of antenna physics.
  • Experience in State Estimation (EKF,UKF) and non-linear optimisation.
  • Ability to read/review C++ code to ensure algorithmic intent is maintained.
  • Experience with RAIM/FDE (Receiver Autonomous Integrity Monitoring).
  • Exposure to CRPA technology and beamforming concepts.
  • SME Authority: Ability to distill complex GNSS phenomena (ionospheric delay, multipath, cycle slips) into actionable engineering requirements.
  • Analytical Rigor: Strong attention to detail regarding error budgets and stochastic modeling.
  • Communication: Ability to explain complex mathematical trade-offs to hardware and software engineers.

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