Firmware Lead - Hardware Acceleration - Lunar Terrain Vehicle

Location: Intuitive Machines HQ, Houston, TX, US

Firmware Lead - Hardware Acceleration - Lunar Terrain Vehicle

(NASA LTVS Award Contingent

Houston, Texas, United States

About Intuitive Machines:

Intuitive Machines is an innovative and cutting-edge space company making cislunar space accessible to both public and private customers. We believe our mission is to further research, communications, and exploration beyond low lunar orbit. With multiple NASA lunar missions in the making and additional private missions on our manifest, we pride ourselves in supporting NASA, our customers and the nation in paving the way to return humans to the surface of the moon. Our world-class team includes experts in all spacecraft subsystems design, development, and test, on-orbit operations, and safety.

We are seeking a Firmware Engineer Lead specializing in Versal Hardware Acceleration to support Intuitive Machines’ Lunar Terrain Vehicle (LTV) program. The LTV is NASA’s next-generation autonomous lunar rover, and this role will focus on developing / leading RTL firmware and software modules for Xilinx Versal ACAP hardware, enabling hardware-accelerated autonomy, vision, and navigation functions in real time.

The successful candidate will work at the intersection of embedded systems, FPGA development, and autonomy software, creating high-performance compute pipelines to process sensor data, support decision-making, and ensure safe rover operations in the lunar environment.

*Employment in this role is contingent upon NASA selecting Intuitive Machines as a winner of LTVS program, scheduled for announcement later in 2025. 

Responsibilities

• Understand self-driving algorithm designs as proposed by the software team, able to dissect, critique, and bend designs to fit hardware capabilities 
• Design, implement, and test hardware acceleration algorithms 
• Understand hardware processing capabilities across multiple modalities (CPU, NPU/AIE, GPU, FPGA, ASIC), quantify relative performance, and recommend ways to optimally distribute algorithms across available flight hardware 
• Analyze hardware performance and produce trade studies for hardware selections and software implementation 
• Rigorously verify the design and performance of hardware acceleration algorithms to ensure compliance with applicable NASA CBCS safety requirements 
• Manage a small team working on all aspects of the above, decomposing a large complex problem into individual problems, assigning them out, and monitoring progress towards completion 

Qualifications

• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, Robotics, or related field (Master’s preferred) 
• Experience with hardware-accelerated algorithm design in aerospace, defense, automotive, robotic, AI, quantitative finance or other contexts 
• Experience certifying hardware-accelerated algorithm design for safety-critical and mission-critical applications 
• Familiar with high-reliability software standards (NPR 7150.2D and NASA-STD-8739.8B and NASA CBCS requirements (e.g. SSP 50038)) 
• Experience with the AMD Versal architecture strongly desired 
• Experience with Nvidia CUDA architecture strongly desired 

Tool/Language Experience: 

• Jira, Jama, Git 
• C, C++ 
• Verilog, VHDL (including RTL design) 
• Vivado Design Suite, Vitis, PetaLinux/Yocto 
• Video/audio codec experience a plus 

Qualifications

• 8+ years of experience in this domain 
• Experience with ROS/ROS2 and integration of hardware acceleration into robotics frameworks.
• Background in computer vision, AI/ML inference (CNNs, SLAM, path planning).
• Familiarity with radiation-tolerant FPGA design practices for space applications.
• Experience in NASA, defense, or spaceflight programs.
• Knowledge of DO-254, DO-178, or equivalent safety-critical development standards.

EEOC

Intuitive Machines is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.