Senior Software Engineer - Navigation and state estimation algorithms
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Key details
- Location
- Sydney, NSW, Australia
- Work style
- Onsite
- Level
- Senior
- Job type
- Full-time
- Experience
- 5–8 yrs
- Function
- Software engineering
- Focus area
- other
- Posted
- 20h ago
Skills
About the role
OVERVIEW OF ROLE
As a Senior Software Engineer at Advanced Navigation, you will operate at the tip of the spear within our 'skunkworks' Special Projects Team. You will fulfill the critical role of developing the highly specialized navigation and state estimation algorithms responsible for processing high-precision sensor signals at the heart of our world-leading products.
You will leverage your deep knowledge acquired through 5+ years of experience in complex technical domains - such as aerospace, autonomous vehicles, or defence systems - to design, implement, and validate advanced sensor fusion architectures. Utilizing your expertise in modern software engineering and mathematical modeling (including C/C++, Python, and MATLAB), you will translate system specifications into robust software solutions for real-time embedded environments. You will augment your software development workflow with robust simulation practices, hardware-in-the-loop (HWIL) testing, and comprehensive uncertainty analysis to ensure all algorithms are verifiably fit for purpose before deployment.
ROLES & RESPONSIBILITIES
- Interpret product and system-level specifications to create software architectures and navigation algorithms that can be executed and tested against.
- Develop and implement stochastic state estimation techniques and advanced algorithms for robust navigation and online sensor calibration.
- Design sensor-fusion solutions utilizing a diverse array of inputs, which may include inertial, magnetic, GNSS, optical, or ranging sensors.
- Develop and evaluate position and orientation estimation algorithms within 6-DOF simulation environments.
- Conduct thorough performance and uncertainty analysis using Monte Carlo simulations and covariance evaluations.
- Anticipate cross-functional impacts and proactively liaise with hardware, system, and production teams to successfully integrate algorithms into embedded platforms.
- Perform hardware-in-the-loop (HWIL) testing and algorithm verification to validate overall system performance.
- Evaluate field and operational test data to identify, analyze, and resolve system anomalies.
- Develop Work Breakdown Structures in Jira and maintain the hygiene of active tickets and assigned tasks.
- Document software architectures, test specifications, and execution procedures for complex systems.
QUALIFICATIONS, EXPERIENCE & SKILLS
- B.Sc., M.Sc., or Ph.D. in Computer Science, Electrical/Electronics Engineering, or a related highly technical field.
- 5+ years of software engineering experience with a strong focus on navigation algorithm development, sensor fusion, or state estimation.
- Programming & Tools: Proficiency in C, C++, and Python, alongside mathematical modeling tools like MATLAB.
- Core Domain Knowledge: Strong foundational understanding of Inertial Navigation Systems (INS), GNSS integration, and sensor calibration methodologies.
- Estimation Techniques: Demonstrated experience developing and deploying robust state estimation algorithms and advanced sensor fusion architectures.
- Simulation & Testing: Experience with 6-DOF simulation, algorithm validation methodologies, and Hardware-in-the-loop (HWIL) setups.
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
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