Computer Vision Engineer II

NASA Jet Propulsion Laboratory

1d•$122,408 - $150,384•Onsite

About The Position

The Computer Vision Engineer II will join the Navigation and Mapping group in JPL’s Guidance and Control Section, part of the Mechanical and Control Systems Division. The role implements image-based mapping and navigation capabilities, applying computer vision to problems such as map-relative localization, hazard detection and avoidance, and 3D structure recovery. The engineer adapts established methods to mission-specific requirements and, where needed, designs and implements novel solutions to new problems. The work supports terrestrial, lunar, Mars-centric, and outer planets missions, with a primary focus on upcoming robotic and human Mars and Moon landing missions. Deliverables have direct mission impact and require a high level of rigor. JPL is located in Pasadena, California, on a campus-like site in the foothills of the San Gabriel Mountains. Its work environment emphasizes innovation, collaboration, and excellence.

Requirements

Bachelor’s degree in Computer Science, Aerospace, Physics, or a related field and at least 3 years of experience; or a master’s degree and at least 1 year of experience; or a Ph.D.
Thorough familiarity with computer vision principles, theories, concepts, and techniques, especially image processing, geometry, or photogrammetry.
Experience with estimation techniques for robotic navigation.
Very strong software skills in C++ and Python.
Hands-on experience with surface-relative navigation sensors, including inertial measurement units, cameras, and lidars.
Ability to work independently with periodic guidance.

Nice To Haves

Experience applying machine learning to computer vision problems.
Background in control theory and space mission design.
Experience participating in multidisciplinary teams.
Good publication record in relevant research areas.
Strong presentation skills.

Responsibilities

Implement image-based mapping and navigation capabilities.
Apply computer vision to map-relative localization, hazard detection and avoidance, and 3D structure recovery.
Adapt standard solutions to problem-specific requirements.
Design and implement novel solutions when existing methods are insufficient.
Deliver code and products for missions with a high level of rigor.