GNC Engineer: Field-Tested Autonomous Drones

Altaares; Paris; On-site; EUR 65,000 - 100,000; Full time

Job summary

Alta Ares is a deeptech startup building real-time AI for defense operations. As a GNC Engineer in Paris, you’ll develop guidance, navigation, and control capabilities for our autonomous platforms, from architecture and flight modelling to live flight testing and operational validation.

You will own end-to-end GNC work, work with operators and end users, and help ensure algorithms perform in real operational conditions, not just in simulations, with short iteration cycles and field validation.

Qualifications

• Minimum 3 years of professional experience in GNC, flight control, robotics, or autonomous systems.
• Solid experience in algorithm development with two or more of MATLAB & Simulink, Python, or C/C++.
• Strong systems engineering skills and aerospace V&V experience.
• Motivation for field testing and deployment on real systems.
• Ability to work autonomously in a fast-paced environment.

Responsibilities

• Design, develop, and improve GNC algorithms for autonomous aerial systems.
• Develop flight dynamics and vehicle models.
• Contribute to system architecture and control strategies.
• Integrate and tune GNC software on target platforms.
• Participate in flight-test campaigns and field demonstrations.
• Analyze flight data and investigate anomalies.
• Collaborate with software, AI, systems engineers, test pilots, and operators for operational validation.

Skills

GNC engineering

Robotics

Systems engineering

Autonomous systems

Tools

MATLAB & Simulink

Python

C/C++

Job description

Alta Ares is a deeptech startup building real-time AI for defense operations. As a GNC Engineer in Paris, you’ll develop guidance, navigation, and control capabilities for our autonomous platforms, from architecture and flight modelling to live flight testing and operational validation.

You will own end-to-end GNC work, work with operators and end users, and help ensure algorithms perform in real operational conditions, not just in simulations, with short iteration cycles and field validation.