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 ROLE

As Advanced Navigation enters a new phase of Growth and International expansion. The Data Fusion Team is on a mission to develop navigation algorithms that ensure our products are the most reliable, high performance navigation products in the world. As a Senior Software Engineer you will be instrumental in realising this ambition, developing software to solve real world problems with real world impact.

ROLES & RESPONSIBILITIES

• Mathematical Translation & Optimisation: Port cutting-edge navigation, sensor fusion, and calibration algorithms from high-level MATLAB prototypes into highly efficient, numerically stable C/C++ implementations using the Eigen library.
• Manage Embedded Compute Constraints: Optimise ported mathematical code to run deterministically within strict real-time execution budgets (e.g., 100Hz–2000Hz loops) and tight memory (SRAM/Flash) footprints on target microcontroller/processor architectures.
• Own the API Boundary: Design and maintain clean, modular C/C++ header interfaces and software libraries that seamlessly integrate core mathematical filters into the broader software platform firmware.
• Drive Algorithmic Test & Validation: Develop comprehensive unit tests, software-in-the-loop (SIL) simulations, and automated regression testing suites using real-world sensor logs to ensure the C/C++ implementation mathematically mirrors the reference MATLAB models.
• Troubleshoot Complex Edge Cases: Investigate and resolve complex algorithmic and embedded software defects, including numerical drift, floating-point overflows, or timing jitter, uncovered during Hardware-in-the-Loop (HIL) testing or field trials.
• Cross-Functional Collaboration: Serve as the technical bridge between algorithm research scientists and core systems/firmware engineers, ensuring design requirements, data definitions, and performance constraints are aligned across teams.
• Modern Workflow Innovation: Proactively adopt and utilise modern AI-assistance tools to optimise coding workflows, code profiling, and technical problem-solving.

QUALIFICATIONS, EXPERIENCE & SKILLS

• Degree qualified Engineer with specialisation in computer systems, software, mechatronics or similar
• Algorithm Translation & Optimisation: A proven track record of translating complex mathematical models (specifically from MATLAB/Python environments) into highly optimised, production-ready C/C++ code.
• Embedded Matrix Operations: Hands-on experience implementing high-frequency linear algebra, matrix manipulations, or coordinate transformations on resource-constrained embedded targets (e.g., ARM Cortex-M/R/A or DSPs).
• Numerical Stability Management: Demonstrated experience handling numerical precision constraints (e.g., managing fixed-point vs. floating-point tradeoffs, preventing underflow/overflow in matrix inversions).
• Production Embedded Systems: 5+ years of engineering experience developing, debugging, and releasing production-quality embedded software running on RTOS or bare-metal platforms.

Skills:

Mandatory

• C/C++ Expert Proficiency: 5+ years of experience writing clean, optimised, and safe code.
• Strong Linear Algebra Foundations: Deep comfort with matrix mathematics, coordinate transformations (ECEF, NED, body frames), and rotation representations (quaternions, Euler angles).
• Eigen Library Proficiency: Proven experience utilising the Eigen C++ template library for high-performance linear algebra operations.
• MATLAB Literacy: Ability to read, interpret, and reverse-engineer complex mathematical prototypes and simulations natively written in MATLAB.

Nice to have

• State Estimation: Practical experience with Kalman Filtering (EKF, UKF) or complementary filters used in sensor fusion.
• Physics/Kinematics: A background in rigid-body dynamics or inertial sensor error modeling (gyroscopes and accelerometers).