Senior GNC Engineer - Modeling and Simulation - Modeling and Simulation

The Role

Mach Industries is seeking a Senior GNC Engineer - Modeling and Simulation to build, validate, and maintain the vehicle models and simulation environments behind GNC development for autonomous aircraft and related defense platforms. You will own significant modeling and simulation workstreams spanning flight dynamics, subsystem models, Monte Carlo analysis, and software- and hardware-in-the-loop testing, with a strong focus on comparing simulation results with flight-test data and turning that data into insights that improve our models and vehicles.

This is a hands-on individual-contributor role with meaningful technical ownership. You will turn equations of motion and engineering data into credible, efficient simulation tools, decide how much fidelity each question requires, and use flight-test data, statistical methods, and machine learning techniques to build the evidence the team needs to trust simulation results in design, verification, and flight-readiness decisions.

The ideal candidate combines strong flight-dynamics and physics-based modeling fundamentals with solid software engineering, data analysis, and practical test experience. You can work independently on complex problems, make sound engineering trade-offs, communicate model limitations and uncertainty clearly, and collaborate effectively with senior technical leaders and partner disciplines.

Key Responsibilities

Simulation Design and Technical Ownership

• Own the development and maturation of assigned simulation capabilities across requirements, architecture, model development, implementation, validation, and use in design and test decisions.
• Translate GNC, vehicle, and mission questions into simulation requirements, fidelity levels, model interfaces, output metrics, and validation criteria.
• Choose the right level of fidelity for each question, from point-mass and three-degree-of-freedom models through high-fidelity six-degree-of-freedom and multi-body simulations, balancing accuracy, run time, maintainability, and schedule.
• Implement equations of motion, reference frames, attitude representations, numerical integration, and event handling for real-time and faster-than-real-time simulation in C/C++ or Rust, along with MATLAB/Simulink.
• Define simulation architecture, model interfaces, data formats, and configuration approaches that allow models to be reused across vehicles and programs.
• Document assumptions, data sources, validity ranges, limitations, and validation evidence so that models and results are clear, reviewable, and reproducible.

Vehicle, Subsystem, and Environment Modeling

• Integrate aerodynamic databases derived from CFD, wind-tunnel testing, and flight data, including blending across flight regimes, damping and dynamic terms, control effectiveness, and behavior at table limits.
• Develop propulsion models for turbine engines, solid rocket motors, or other propulsion systems, covering thrust, fuel flow, throttle and derate behavior, thrust misalignment, jet damping, and gyroscopic effects.
• Work with Mechanical Engineering to maintain mass-property models, including center-of-gravity and inertia variation with fuel burn, expended components, and configuration changes.
• Model actuators and effectors, including bandwidth, rate and position limits, deadband, backlash, hysteresis, latency, and failure modes.
• Model IMUs, GNSS receivers, air-data sensors, seekers, and other sensors with representative noise, bias, scale-factor error, misalignment, latency, quantization, and failure behavior.
• Model atmosphere, winds, turbulence, and gusts, and incorporate weather data where mission analysis requires it.
• Model structural modes, launch and recovery systems, separation and deployment events, and other multi-body or constrained dynamics where they affect GNC performance.

Monte Carlo Analysis and Simulation Tools

• Plan and execute Monte Carlo analyses with defined dispersions on aerodynamics, mass properties, propulsion, sensors, actuators, winds, and initial conditions.
• Maintain uncertainty models and dispersion databases with documented sources, distributions, bounds, and rationale.
• Maintain data pipelines that bring aerodynamic, mass-property, propulsion, and test data into the simulation, with validation checks at each step.
• Build and improve tools for batch execution, parameter sweeps, sensitivity studies, statistical post-processing, and visualization of large simulation datasets.
• Make results deterministic, reproducible, and easy to find, compare, and share by managing random seeds, configuration files, model versions, input data, and software versions.
• Establish automated regression tests and clear pass/fail criteria for models, simulation scenarios, and GNC software changes as part of continuous integration.
• Profile and improve simulation performance so that large studies run efficiently on workstations and shared or cloud compute resources.

Validation and Test Support

• Lead the comparison of simulation predictions with flight-test data, reconstructing flights in simulation with the as-flown vehicle configuration, software, mass properties, winds, and commands.
• Quantify model error across the flight envelope, identify the sources of discrepancies, and drive evidence-based updates to models, uncertainty bounds, and dispersions.
• Turn flight-test data into actionable insights about vehicle performance, aerodynamics, propulsion, sensors, actuators, and GNC behavior, and communicate findings that shape design and test decisions.
• Apply machine learning and statistical techniques, such as regression, clustering, anomaly detection, and data-driven or surrogate modeling, to uncover trends and unexpected behavior across flight-test and simulation datasets.
• Build automated workflows that ingest flight logs, align them with simulation results, compute correlation metrics, and report findings quickly after each flight.
• Perform system identification and parameter estimation to build and update plant, actuator, propulsion, and sensor models from flight and ground-test data.
• Establish verification and validation approaches for simulation models, including unit tests, analytical checks, code-to-code comparisons, and comparison with component and ground-test data.
• Develop and support software-in-the-loop and hardware-in-the-loop environments that run flight software against the vehicle simulation with representative timing, interfaces, and fault injection.
• Support flight-test planning with pre-flight predictions, envelope and test-point analysis, and simulated rehearsals of nominal and off-nominal scenarios.

Technical Judgment and Team Contribution

• Independently identify risks, dependencies, missing inputs, and technical blind spots within assigned work, then propose and drive practical paths to resolution.
• Make timely, defensible recommendations about model fidelity and simulation results while clearly communicating assumptions, uncertainty, evidence, and residual risk.
• Partner with Guidance, Navigation, Controls, Aerodynamics, Propulsion, Mechanical Engineering, Systems Engineering, Avionics, Embedded Software, Software Infrastructure, and Test to define model needs, data sources, and interfaces.
• Support vehicle trade studies, mission and engagement analyses, and concept-of-operations studies with simulation results that isolate the effects under consideration.
• Lead focused model reviews and root-cause investigations for assigned areas.
• Review the work of other engineers, mentor less-experienced team members, and contribute reusable tools, methods, documentation, and standards.
• Escalate unresolved issues when they threaten technical performance, flight safety, or program milestones.

Required Qualifications 

• Bachelor's degree in aerospace engineering, mechanical engineering, electrical engineering, physics, applied mathematics, computer science, or a related technical field.
• Substantial experience developing, validating, or using physics-based simulations of aircraft, missiles, launch vehicles, spacecraft, or other dynamic systems, typically gained through 5 or more years of relevant work.
• Strong understanding of rigid-body dynamics, flight mechanics, aerodynamics, reference frames, attitude representations, and numerical integration.
• Experience developing six-degree-of-freedom simulations and integrating aerodynamic, propulsion, mass-property, actuator, sensor, and environmental models.
• Experience with Monte Carlo analysis, uncertainty modeling, sensitivity studies, and statistical analysis of simulation results.
• Experience comparing simulation results with flight-test data, explaining discrepancies, and using system identification or parameter estimation to improve model accuracy.
• Experience analyzing large flight-test or telemetry datasets, including time alignment, filtering, and statistical methods.
• Experience with software-in-the-loop or hardware-in-the-loop simulation of flight software or embedded systems.
• Proficiency in C/C++ or Rust, along with MATLAB/Simulink, for simulation development, automation, and data analysis.
• Fluency with modern engineering workflows, including Git, code review, continuous integration, issue tracking, and configuration management.
• Demonstrated ability to own complex technical work, communicate across disciplines, and drive issues to closure.

Preferred Qualifications 

• Master's degree in aerospace engineering, mechanical engineering, applied mathematics, or a related field.
• Experience developing simulations for autonomous fixed-wing aircraft, missiles, launch vehicles, spacecraft, or high-performance unmanned systems.
• Experience applying machine learning, data-driven modeling, or advanced statistical methods to flight-test, telemetry, or simulation data.
• Experience with JSBSim, PX4 software-in-the-loop, Simscape, or similar simulation frameworks.
• Experience developing aerodynamic databases from CFD, wind-tunnel, or flight-test data.
• Experience modeling turbine engines, solid rocket motors, or other propulsion systems.
• Experience modeling radar, electro-optical, or infrared seekers, or simulating target engagements.
• Experience with multi-body dynamics, structural modes, launch and recovery systems, or separation events.
• Familiarity with orbital mechanics or satellite constellation modeling.
• Experience running large simulation campaigns on cluster or cloud computing resources, including containerization and simulation data management.

What Success Looks Like

Within your first year, you will have:

• Taken clear ownership of one or more significant simulation capabilities and advanced them through development, validation, and use in design and test decisions.
• Delivered validated vehicle, subsystem, and environment models with documented sources, validity ranges, and uncertainty.
• Established a repeatable workflow for comparing simulation with flight-test data and used it to measurably improve model accuracy, uncertainty bounds, and dispersions.
• Turned flight-test data into insights, including results from statistical or machine learning analysis, that informed design, test, or GNC decisions.
• Made Monte Carlo and simulation workflows faster, more reproducible, and easier for the team to use and trust.
• Strengthened SIL or HIL testing and automated regression coverage for GNC software and simulation changes.
• Communicated model limitations, technical conclusions, and risks clearly, enabling timely program decisions.
• Made the GNC team more effective through reusable tools, thoughtful reviews, mentorship, and dependable execution.

Additional Requirements

Engineer 180000 - 210000 USD