Must be a US Person or Permanent Resident
W2 with full benefits - 1 year contract position with potential for extension or conversion
Customer and contract specific training will be required and provided.
Location - Pasadena, CA (Onsite)
Offer contingent on ability to successfully pass a background check and drug screen
LCAT - Computer Vision and Machine Learning Engineer
The US base salary range for this full-time position is $63.80-$102.15/hr + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Responsibilities:
· Develop and implement algorithms integrating Computer Vision (CV) and Machine Learning (ML) in support of guidance, navigation and control for spacecraft landing on planetary bodies.
. Includes image-based hazard detection (HD)
. Includes map-relative localization
· Implement and test CV and ML solutions in support of broader GN&C objectives.
· Create high-fidelity simulations to validate HD and other vision algorithms.
Qualifications:
Required Skills:
· Bachelor’s degree in a technical discipline with 6 years of relevant experience, or a Masters degree with 4 years of relevant experience, or a Ph.D. with 2 years of relevant experience.
· Strong technical background in computer vision and machine learning with specific application to space or space-based systems.
· Extensive experience in Software Engineering and the practical implementation of Machine Learning or Computer Vision including for real-time applications.
· Proven track record in development, testing, and validation of autonomous, vision-based algorithms in complex environments.
· Excellent communication and interpersonal skills, with a proven ability to present findings to diverse stakeholders.
Desired Skills:
· Experience with Terrain Relative Navigation (TRN) and the integration of vision-based sensors into closed-loop GNC architectures.
· Demonstrated experience in technical leadership and managing project resources or mission-specific deliverables.
· Expertise in the calibration and error-budgeting of sensors including IMUs, SRUs, LIDAR, and Vision systems.