Description:

Perceptive Space Systems is developing a decision intelligence platform to assist satellite and launch operators in navigating risks from space weather and the space environment.
The company operates at the intersection of aerospace, AI, and real-time systems, utilizing advanced modeling, sensor fusion, and autonomy to enhance operational resilience in orbit.
The role involves building foundational technology for satellites, launch vehicles, and human missions to ensure safe and efficient operations in space.
The position focuses on creating advanced navigation and state estimation systems for next-generation space vehicles and sensing platforms.
The ideal candidate will be part of a small, high-velocity team, addressing real-world challenges with immediate mission impact.
Responsibilities include designing and implementing probabilistic filtering techniques for state estimation, developing sensor fusion algorithms, and contributing to architecture development and technology trade studies.
Collaboration with AI/ML engineers to explore machine learning-enhanced state estimation techniques is also part of the role.

Requirements:

Candidates must have strong proficiency in state estimation techniques, including Kalman filtering and batch filtering.
Expertise in non-linear optimization and computational mathematics is required.
Proficiency in both Python and C/C++ is necessary.
Experience with GNSS, radar, lidar, and camera data, including sensor calibration and error modeling, is essential.
Familiarity with modern software engineering practices such as version control (Git), CI/CD, cloud-based workflows, and peer review is required.
A minimum of 4 years of industry experience is needed, along with a Master’s or PhD in Aerospace Engineering, Electrical Engineering, Mechatronics, or a related field.
Excellent communication and collaboration skills are necessary for effective interdisciplinary work.
Experience in a fast-paced, process-oriented, high-ownership startup environment is preferred.
Preferred qualifications include experience with uncertainty quantification, Monte Carlo methods, machine learning frameworks, spacecraft guidance, navigation, and control, as well as familiarity with Rust or Go.
Applicants must be U.S. Citizens or Permanent Residents, as visa sponsorship is not available for this position.