Compensation: Competitive salary, benefits, and equity package
About the Role
We are seeking a highly skilled Astrodynamics Engineer to serve as a technical leader in orbital mechanics, orbit determination, and space domain awareness applications. This role will be responsible for developing and validating dynamic models, generating synthetic datasets, supporting mission analysis, and advancing orbit estimation capabilities across a variety of orbital regimes, including near-Earth and cislunar environments.
The ideal candidate combines deep expertise in astrodynamics with strong analytical and programming skills and can collaborate effectively with software engineers, data scientists, and external research partners. This position plays a critical role in ensuring that orbital modeling, estimation, and simulation products are scientifically rigorous, operationally relevant, and suitable for advanced analytics and machine learning applications.
Key Responsibilities
- Develop and validate dynamical modeling environments spanning multiple orbital regimes, including two-body, perturbed LEO/GEO, and multi-body cislunar dynamics.
- Generate high-fidelity synthetic observation datasets, incorporating realistic sensing geometries, visibility constraints, measurement noise, observation gaps, and degraded sensing conditions.
- Utilize publicly available ephemerides and reference datasets to validate simulation and propagation frameworks.
- Design, implement, and evaluate orbit determination and state-estimation algorithms using appropriate estimation methodologies.
- Analyze estimator performance, convergence behavior, covariance evolution, observability limitations, and custody feasibility.
- Define and characterize anomalous orbital behavior using physics-based approaches to support downstream detection, classification, and analytic capabilities.
- Collaborate with software engineering and data science teams to ensure simulation outputs and training datasets accurately represent real-world orbital dynamics.
- Provide astrodynamics expertise to support concept of operations (CONOPS), system engineering, mission planning, and performance assessments.
- Establish technical interfaces, validation methods, and collaboration frameworks with external research organizations and academic partners.
- Document modeling assumptions, validation results, and engineering analyses to support program objectives and technical reviews.
Required Qualifications
- Master’s degree or PhD in Aerospace Engineering, Astrodynamics, Applied Mathematics, Physics, or a related technical discipline.
- 3+ years of relevant experience in astrodynamics, orbit determination, mission analysis, or space domain awareness applications. Advanced research experience may be considered in lieu of professional experience.
- Demonstrated expertise in orbit determination methodologies, including batch least-squares and sequential/Kalman-filter-based estimation techniques.
- Strong understanding of covariance analysis, estimation theory, and observability assessment.
- Working knowledge of orbital mechanics across multiple regimes, including:
- Low Earth Orbit (LEO)
- Geostationary Earth Orbit (GEO)
- Invariant manifolds and periodic orbit families
- Experience addressing sparse-observation and short-arc orbit determination challenges.
- Strong programming skills in Python, with experience in scientific computing and numerical analysis.
- Familiarity with C/C++, MATLAB, Julia, or similar technical computing environments.
- Experience modeling optical observations, sensor measurement characteristics, visibility constraints, and observational error sources.
- Ability to obtain and maintain a U.S. Government security clearance.
Preferred Qualifications
- Direct experience supporting cislunar, XGEO, or advanced space domain awareness missions.
- Knowledge of normal-form methods, Lie-series techniques, or other advanced dynamical systems analysis approaches.
- Experience collaborating with universities, research institutions, or government-funded research programs.
- Experience developing synthetic datasets for machine learning, AI, or advanced analytics applications.
- Understanding of techniques to identify and mitigate bias or unintended structure in training datasets.
- Publication record in astrodynamics, orbital mechanics, or space domain awareness conferences and journals such as AIAA, AAS, or AMOS.
- Experience supporting operational space surveillance, catalog maintenance, or custody-tracking systems.
What We Offer
- Opportunity to work on advanced space technology and orbital analytics challenges.
- Collaborative, mission-driven environment with significant technical ownership.
- Exposure to cutting-edge developments in astrodynamics, mission analysis, and space domain awareness.
- Competitive compensation package, including salary, benefits, and equity opportunities.
- Professional growth and leadership opportunities within a rapidly expanding technology organization.