Computer Vision and Machine Learning Engineer (Onsite)

Overview

• Must be a U.S. 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

Position

• LCAT – Computer Vision and Machine Learning Engineer

Salary

• US base salary range for this full-time position is $63.80‑$102.15/hr + benefits.
• Salary ranges are determined by role, level, and location.
• The range displayed reflects the minimum and maximum target for new hire salaries 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 Master's 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.