GNC Engineer III (Mendon)

ConsultNet Technology Services and Solutions; Mendon (UT); Hybrid; USD 73,000 - 95,000; Full time

Job summary

ConsultNet Technology Services and Solutions seeks a GNC Engineer III in Cache County, UT. This contract role focuses on developing, integrating, and validating Guidance, Navigation, and Controls algorithms for autonomous heavy equipment.

You will work on vehicle dynamics, state estimation, trajectory planning, and path tracking, with cross-functional collaboration and exposure to SIL/HIL testing and field validation.

Qualifications

• Bachelor's degree in a related technical field is required.
• 5+ years in controls, navigation, robotics, or autonomous systems.
• Strong understanding of control theory, stability, and dynamics.
• Proficiency in C++ and Python; experience with MATLAB/Simulink.

Responsibilities

• Develop, integrate, tune, and validate GNC algorithms for autonomous vehicles.
• Design and tune feedback-control systems for stability and performance.
• Develop localization and state-estimation solutions using GNSS/IMU/odometry.
• Support trajectory generation, path planning, and motion planning.
• Collaborate across subsystems and with field teams; perform testing and validation.
• Create tools for simulation, data processing, and automated testing.

Skills

C++

Python

Control theory

Localization

State estimation

Trajectory planning

Vehicle dynamics

Linux

Education

Bachelor's degree in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Robotics, Computer Engineering, Computer Science, or a related technical field

Tools

MATLAB/Simulink

ROS/ROS2

Linux

Job description

Title: Guidance, Navigation & Controls (GNC) Engineer III
Location : Cache County, UT (hybrid, onsite 3x/wk)
Target Start Date : ASAP
Type: Contract (2-3+ years)
Pay Rate : $52.54-$69.38/hr

Job Summary

Our client, a global leader in advanced autonomous and robotic solutions across multiple industries, is seeking a GNC Engineer III to develop, integrate, and validate Guidance, Navigation, and Controls algorithms for autonomous heavy-equipment applications. This role focuses on vehicle dynamics, localization, state estimation, trajectory planning, path tracking, and control systems to enable safe, accurate, and reliable autonomous operation across challenging terrain and operating conditions.

Responsibilities

• Develop, integrate, tune, and validate GNC algorithms for autonomous vehicle applications.
• Develop motion-control capabilities including path tracking, trajectory following, steering, propulsion, braking, and speed control.
• Design and tune feedback-control algorithms to improve stability, accuracy, responsiveness, and performance.
• Develop localization and state-estimation solutions using GNSS/GPS, inertial sensors, odometry, encoders, and other vehicle data.
• Contribute to trajectory generation, path planning, and motion-planning solutions.
• Develop vehicle-dynamics and system models for controller design, simulation, and performance analysis.
• Integrate GNC algorithms with perception, task planning, embedded software, vehicle-control systems, and other subsystems.
• Evaluate performance using simulation, software-in-the-loop (SIL), hardware-in-the-loop (HIL), recorded-data replay, and field testing.
• Analyze vehicle logs and field data to identify performance issues, localization errors, control instability, and edge cases.
• Develop tools and scripts for simulation, data processing, visualization, automated testing, controller tuning, and performance analysis.
• Troubleshoot issues involving control behavior, localization, sensor timing, coordinate systems, and system integration.
• Own assigned GNC features through development, integration, testing, and field validation.
• Document algorithms, mathematical models, software interfaces, test results, and system limitations.
• Collaborate with cross-functional engineering and field teams through design reviews, code reviews, testing, and technical investigations.

Requirements

• Bachelor's degree in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Robotics, Computer Engineering, Computer Science, or a related technical field.
• 5+ years of experience in controls, navigation, robotics, vehicle dynamics, state estimation, or autonomous systems.
• Strong understanding of control theory, including feedback control, PID control, stability, and system dynamics.
• Experience developing and tuning control algorithms on physical robotic, automotive, aerospace, industrial, or heavy-equipment systems.
• Experience with localization, navigation, trajectory generation, path tracking, or state estimation.
• Proficiency in C++ and Python and experience with MATLAB/Simulink or comparable engineering tools.
• Experience developing software in Linux-based environments.
• Familiarity with ROS/ROS2 or comparable robotics middleware.
• Understanding of coordinate systems, transformations, vehicle kinematics, and vehicle dynamics.
• Experience with simulation and test data analysis, version control, automated testing, and continuous integration.
• Strong analytical, mathematical, troubleshooting, and communication skills.

Preferred Qualifications

• Advanced degree in Engineering, Robotics, Controls, or a related discipline.
• Experience with autonomous vehicles, construction equipment, heavy machinery, mobile robots, or off-road platforms.
• Experience with Kalman filters, EKF, particle filters, or other state-estimation techniques.
• Experience with GNSS/RTK, IMUs, odometry, encoders, and multi-sensor localization.
• Experience with model-based design, system identification, controller tuning, or vehicle-dynamics modeling.
• Knowledge of optimization-based control, model predictive control, trajectory optimization, or motion planning.
• Experience integrating algorithms with vehicle-control units, embedded controllers, CAN networks, or drive-by-wire systems.
• Experience with SIL, HIL, and recorded-data replay testing.
• Familiarity with functional safety and validation of autonomous or safety-critical systems.

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