Staff System Modeling Engineer, Warfighter Systems

About the team

Our Warfighter Systems division is pioneering a future where mixed reality (MR), creates immersive, intuitive, and life-saving technologies. By seamlessly integrating real-time data with cutting-edge visualization tools, we are empowering warfighters with unparalleled situational awareness, enhanced training experiences, and operational superiority. This team is consistently pushing the boundaries of what's possible and shaping a future where technology and defense unite to protect our nation.

About the job

We are seeking a highly skilled and experienced System Modeling Engineer to design, develop, and validate sophisticated models for complex electro-mechanical systems, with a particular focus on sensors, cameras, and actuators. The ideal candidate will leverage first-principles physics, empirical data, and advanced mathematical techniques to create high-fidelity, predictive models used across the entire product lifecycle – from concept exploration and design optimization to control system development and virtual testing. This role is critical in accelerating our product development cycles, improving system performance, and ensuring robust and reliable operation.

What you'll do

• Model Development:
  • Develop mathematical and behavioral models for various sensor types (e.g., IMU, Lidar, Radar, Ultrasonic, environmental sensors), capturing characteristics such as noise, latency, calibration, field of view, and transfer functions.
  • Create detailed camera models, encompassing optics, image signal processing pipelines, distortion, resolution, dynamic range, and temporal characteristics.
  • Build dynamic models for various actuator types (e.g., motors, hydraulics, pneumatics, solenoids), including their mechanical, electrical, and thermal behavior, force/torque output, precision, and bandwidth limitations.
  • Integrate individual component models into comprehensive system-level simulations, accurately representing their interactions and overall system dynamics.
  • Develop and maintain Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) simulation environments.

• Model Validation & Calibration:
  • Design and execute experiments to gather real-world data for model parameter identification, calibration, and validation.
  • Perform rigorous statistical analysis to quantify model accuracy, uncertainty, and fidelity against empirical measurements.
  • Identify discrepancies between model predictions and real-world behavior and iteratively refine models for improved accuracy.

• Performance Analysis & Optimization:
  • Conduct trade-off studies using models to optimize system architecture, component selection, and control strategies based on performance, cost, power consumption, and reliability metrics.
  • Predict system performance under various operating conditions and environmental factors.
  • Perform sensitivity analyses to understand the impact of individual parameters on overall system behavior.
  • Support root cause analysis of system issues using simulation.

• Collaboration & Communication:
  • Collaborate closely with cross-functional teams including Electrical, Mechanical, Controls, Software, and Test Engineers to define model requirements and integrate models into the broader development process.
  • Clearly communicate complex modeling concepts, results, and limitations to both technical and non-technical stakeholders through presentations and detailed documentation.

• Tooling & Methodologies:
  • Select, evaluate, and implement appropriate modeling and simulation tools and techniques.
  • Develop custom scripts and tools to enhance modeling capabilities and automate workflows.
  • Stay abreast of industry best practices, new modeling methodologies, and emerging simulation technologies.

Required Qualifications

• 6+ years of experience in system modeling, simulation, and analysis, particularly with electro-mechanical systems.

• Demonstrated experience in developing models for at least two of the following:
  • Sensors: IMUs (accelerometers, gyros), Lidars, Radars, Ultrasonic sensors, force/torque sensors, etc. (noise characteristics, drift, latency, sensor fusion).
  • Cameras: Optical models, image processing pipeline models, distortion, noise, dynamic range, rolling shutter effects.
  • Actuators: DC/BLDC motors, stepper motors, servo motors, hydraulic/pneumatic systems, gearing, linkages (dynamics, thermal effects, efficiency, bandwidth).

• Strong theoretical foundation in classical and modern control systems, dynamics, signal processing, and numerical methods.

• Proficiency in primary modeling and simulation tools such as MATLAB/Simulink (Simscape a plus), Python (SciPy, NumPy, Pandas), or C/C++.

• Experience with model validation against experimental data and statistical analysis techniques.

• Excellent problem-solving skills, with an ability to apply first principles to complex engineering challenges.

• Strong communication and interpersonal skills, with the ability to work effectively in a team environment. Strong technical communication skills to collaborate effectively with cross-functional teams.

• U.S. Person Status: Due to government contract requirements, candidates must be a U.S. Person (U.S. Citizen or Green Card holder).

• Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, Physics, or a related quantitative field.

Preferred Qualifications

• Ph.D. in a relevant engineering or scientific discipline.

• Experience with Modelica, Adams, Amesim, Gazebo, or other advanced multi-domain simulation tools.

• Familiarity with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing methodologies and platforms (e.g., dSPACE, National Instruments).

• Knowledge of advanced control techniques (e.g., adaptive control, optimal control, robust control) and estimation algorithms (e.g., Kalman filters, particle filters).

• Experience with machine learning techniques for model identification, surrogate modeling, or data-driven predictions.

• Exposure to systems engineering processes, requirements management, and configuration control.

• Experience with cloud-based simulation platforms or distributed computing for large-scale simulations.