Senior DSP & Controls Engineer - Guidance, Navigation & Control

Advanced Navigation; Sydney; On-site; AUD 150,000 - 210,000; Full time

Job summary

Advanced Navigation is seeking an engineer to develop and advance control and signal processing solutions for Fibre Optic Gyroscopes (FOG). You will work in a multidisciplinary team to improve sensor performance, robustness and reliability through modelling, algorithm development and experimental validation.

The role emphasizes optimizing closed-loop control and digital signal processing for real-time hardware and translating requirements into FPGA-based designs.

Qualifications

• Degree in control engineering, electrical or electronic engineering, physics, applied mathematics, or a related discipline.
• Demonstrated experience developing control and DSP solutions for real-time systems.
• Strong capability in mathematical modelling, simulation and experimental data analysis.
• Practical experience validating algorithms on hardware and resolving system-level performance issues.
• Proficiency in MATLAB/Simulink, Python, or equivalent engineering tools.
• Ability to work independently and collaboratively within a multidisciplinary team.
• Experience with Fibre Optic Gyroscopes, inertial sensors, optical instrumentation or precision measurement systems.
• Familiarity with FPGA or embedded implementations of control and signal processing algorithms.
• Experience supporting product development from prototype through verification and production.

Responsibilities

• Develop and optimize closed-loop control and DSP algorithms for FOG performance.
• Develop models and analysis methods to understand system behaviour and guide design decisions.
• Investigate performance limitations and deliver improvements through structured analysis and experimental validation.
• Collaborate with photonics, electronics, FPGA and firmware engineers to translate algorithm concepts into real-time solutions.
• Define performance requirements and verification approaches, ensuring solutions meet system and product needs.
• Support system integration, characterisation and troubleshooting throughout development and production.
• Provide technical ownership across the development lifecycle, from concept and feasibility studies through implementation, verification and production support.
• Take ownership of assigned technical work packages, including planning, risk management, documentation and delivery.

Skills

Control theory & DSP

Real-time systems

Mathematical modelling

Data analysis

Hardware validation

MATLAB/Simulink

Python

Independent + collaborative

Inertial sensors familiarity

FPGA/embedded DSP

Product lifecycle

Education

Degree in control engineering, electrical or electronic engineering, physics, applied mathematics, or a related discipline

Tools

FPGA toolchains

Hardware prototyping

Job description

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

This role is responsible for developing and advancing control and signal processing solutions for Fibre Optic Gyroscopes (FOG). Working within a multidisciplinary engineering team, the engineer will improve sensor performance, robustness and reliability through modelling, algorithm development and experimental validation. The role focuses on optimising closed-loop control and digital signal processing to improve FOG performance, stability and dynamic response. It also translates system requirements into algorithm designs and specifications for FPGA implementation.

Key Responsibilities

• Develop and optimize closed-loop control and digital signal processing algorithms, including signal acquisition and timing, to meet FOG performance requirements.
• Develop models and analysis methods to understand system behaviour and guide design decisions.
• Investigate performance limitations and deliver improvements through structured analysis and experimental validation.
• Collaborate with photonics, electronics, FPGA and firmware engineers to translate algorithm concepts into practical, real-time solutions.
• Define performance requirements and verification approaches, ensuring solutions meet system and product needs.
• Support system integration, characterisation and troubleshooting throughout development and production.
• Provide technical ownership across the development lifecycle, from concept and feasibility studies through implementation, verification and production support.
• Take ownership of assigned technical work packages, including planning, risk management, documentation and delivery.

Essential Experience and Skills

• Degree in control engineering, electrical or electronic engineering, physics, applied mathematics, or a related discipline.
• Demonstrated experience developing control and digital signal processing solutions for real-time systems.
• Strong capability in mathematical modelling, simulation and experimental data analysis.
• Practical experience validating algorithms on hardware and resolving system-level performance issues.
• Proficiency in MATLAB/Simulink, Python, or equivalent engineering tools.
• Ability to work independently and collaboratively within a multidisciplinary team.
• Experience with Fibre Optic Gyroscopes, inertial sensors, optical instrumentation or precision measurement systems.
• Familiarity with FPGA or embedded implementations of control and signal processing algorithms.
• Experience supporting product development from prototype through verification and production.

Soft Skills

• Good communication and interpersonal skills with the ability to work effectively across multiple engineering disciplines.
• Ability to collaborate in a highly integrated multidisciplinary team environment.
• Proactive approach to problem solving and continuous improvement.
• Strong ownership mindset and accountability for technical outcomes.
• Commitment to knowledge sharing, mentoring, and fostering a collaborative engineering culture.