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Intuitive Machines

Perception Software Lead - Lunar Terrain Vehicle

Intuitive Machines, Glen Burnie, Maryland, United States, 21060

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Perception Software Lead - Lunar Terrain Vehicle Houston, Texas

About Intuitive Machines Intuitive Machines is an innovative and cutting‑edge space company making cislunar space accessible to both public and private customers. Our mission is to further science, exploration, communications, and economic progress from the Earth to the Moon and beyond. With the first commercial lunar landing in history, multiple NASA lunar missions in development, and additional private missions on our manifest, we pride ourselves in supporting our customers and the nation in paving the way to return humans to the surface of the Moon.

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

About The Role Lead a small team in the development and certification of the LTV perception system, fusing data from LiDARs, cameras, and IMUs into a single coherent map of the rover’s surroundings.

Responsibilities

Proactively identify and document requirements for the vehicle perception system

Architect and decompose the software solution for vehicle perception

Coordinate the testing and certification of the system

Comfortable developing software in a high‑reliability environment, compliant to NASA standards NPR 7150.2D and NASA-STD-8739.8B and NASA CBCS requirements (e.g. SSP 50038)

Represent perception software at NASA safety panels

Supervise several internal employees and contractors

Qualifications

Bachelor's degree in computer science, computer engineering, etc.

Expertise in machine vision, sensor fusion, and Simultaneous Localization and Mapping (SLAM), including LiDAR‑inertial and visual‑inertial odometry

Experience ingesting, processing, and fusing data from monocular and stereoscopic imaging systems, LiDARs, IMUs, Star Trackers, and GP

Sensor fusion techniques, including classical Kalman filters, multiplicative Kalman filters, and pose graph optimization

Failure Detection, Isolation, and Response (FDIR) logic for all‑of‑the‑above

Experience in verification by simulation for complex perception systems

Development and maintenance of high‑quality design and testing documentation

Demonstrated relevant project experience (planetary rovers, autonomous vehicles, robotics, etc.)

Language / Tool Experience

C or C++ (required)

Python or other modeling/analysis languages (nice to have)

Familiar with FPGA, GPU, and NPU hardware acceleration techniques for algorithms and able to coordinate with hardware acceleration engineers to implement and validate algorithms

Git, Jira, Jama

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.

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