GNC Engineer - AI Applications

Title: GNC Engineer - AI Applications
Location : Lehi, UT (hybrid - 3x/wk onsite. Relocation assistance package)
Target Start Date : ASAP
Type: Contract-to-Hire (Direct Hire possible)
Pay Rate : $80.00-$95.00/hr
Salary: $165K-$195K

GNC Engineer IV - AI Applications

Overview
Our client, a global leader in advanced autonomous and robotic solutions and creator of the industry's most advanced unmanned command and control solution for vehicle operations, is seeking a senior GNC Engineer to apply AI and machine learning techniques to guidance, navigation, and control systems for autonomous robotic platforms. This role focuses on vehicle dynamics, precision control, and real-time behavior, bridging AI research and production systems to deliver high-performance autonomy in safety-critical environments.

• Design and implement AI-driven guidance, navigation, and control algorithms to improve autonomy, stability, and decision-making.
• Integrate machine learning models with vehicle dynamics, sensor systems, and simulation environments.
• Embed AI-based GNC capabilities into production software platforms, ensuring alignment with perception, planning, and control modules.
• Convert trained models into production-ready services, APIs, or embedded libraries for real-time GNC use cases.
• Optimize algorithms for real-time performance, low latency, and reliability in safety-critical robotic systems.
• Collaborate with robotics, controls, AI, and software teams across research and product-focused environments.
• Validate GNC systems using simulation, hardware-in-the-loop, and field testing.
• Monitor deployed systems and continuously refine models, algorithms, and tuning parameters to improve control quality and autonomous performance.

• Bachelor's degree in Robotics, Aerospace Engineering, Mechanical Engineering, Computer Science, or a related technical field.
• 10 years of GNC engineering experience, including 2-5 years applying AI/ML to robotics or dynamic systems.
• Strong programming experience with Python (required); C , C, and ROS highly preferred.
• Hands-on experience with AI/ML frameworks such as PyTorch or TensorFlow.
• Deep foundation in control theory, vehicle dynamics, navigation, and localization algorithms.
• Proven experience integrating AI models into real-time or near-real-time systems.
• Strong analytical skills and ability to translate system behavior into robust technical solutions.
• Effective collaborator in cross-functional, fast-growing engineering teams.

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