GN&C (Guidance, Navigation, and Control) Engineer

Aerospace Mid-level (L4 equivalent) 2-5 years

1 Which company are you aiming at?

To generate precise rejection-prevention feedback and application strategy, tell us where you're targeting.

SpaceX

Boeing

Lockheed Martin

Blue Origin

Northrop Grumman

Rocket Lab

2 Send your application

You need an account so we know where to send the feedback.

Create an account Sign in

The job description

Tech stack. MATLAB/Simulink, 6-DOF simulation, Kalman filtering libraries, sensor models (IMU, star tracker, GPS), HIL test benches, Python

About the role

You will join the GN&C team of an aerospace company responsible for knowing where the vehicle is, where it needs to go, and making it go there. The team owns navigation algorithms, guidance laws, and control systems from design through flight validation. This role matters because GN&C is the brain of every aerospace vehicle: your estimators and controllers decide whether a rocket lands on the pad, a satellite points at its target, or an aircraft holds its trajectory in turbulence. You will design algorithms that must work the first time in environments you cannot fully replicate on the ground, which demands mathematical rigor and engineering humility in equal measure. Your simulations will include the ugly realities: sensor biases that drift, actuators with deadbands and saturation, flexible modes coupling into control loops, and faults occurring at the worst possible moment. You will work closely with flight software engineers to ensure elegant algorithms survive implementation in fixed-point arithmetic and real-time deadlines. When flight data arrives, you will compare it against predictions with ruthless honesty, because the gap between the two is where the real learning lives.

What you will achieve

Deliver GN&C algorithms meeting pointing, navigation accuracy, and stability requirements with Monte Carlo validation across dispersions
Cut estimator tuning time by 30 percent through systematic covariance analysis and automated filter performance assessment
Own 6-DOF closed-loop simulation with sensor and actuator models correlated to hardware test data
Drive HIL testing campaigns that retire GN&C risk before flight: fault injection, sensor dropout, and contingency modes all verified
Ship flight software requirements and verification evidence supporting certification or customer acceptance
Improve navigation robustness by designing fault detection and isolation logic validated against injected sensor and actuator failures

What you will bring

Must-haves

2 to 5 years of experience in GN&C, navigation, or control systems for aerospace vehicles
Deep understanding of estimation theory: Kalman filtering (EKF/UKF), sensor fusion, and covariance analysis
Strong control theory fundamentals: classical and modern methods, stability margins, and robust control basics
Proficiency with MATLAB/Simulink for algorithm development and 6-DOF simulation
Working knowledge of inertial sensors, GNSS, star trackers, and their error characteristics
Experience with Monte Carlo analysis for dispersions, robustness, and requirements verification
Ability to translate flight requirements into algorithm specifications and test criteria

Nice-to-haves

Experience with rendezvous, proximity operations, or precision landing guidance
Knowledge of fault-tolerant GN&C architectures and FDIR design
Familiarity with flight software development processes (DO-178C)
Exposure to optical navigation or terrain-relative navigation
Experience with vision-based navigation or terrain-relative navigation methods