Overview In this role, you will architect and guide end-to-end remote sensing and exploitation pipelines for space observation analytics. You'll lead multi-disciplinary teams, shaping next gen tools that fuse imaging physics with ML-based behavior inference to accelerate mission outcomes. Expect to tackle challenging imaging, multi-sensor fusion, and trajectory modeling in a collaborative environment. Your work drives secure, reliable, user-centric tools that deliver high-fidelity insights for EO/IR missions.
Compensation / Benefits- health benefits
- life and disability benefits
- financial and retirement benefits
- paid leave
- professional development
- tuition assistance
Responsibilities- Architect end-to-end remote sensing processing systems for EO/IR missions
- Lead development of radiometric and spectral response models
- Oversee advanced imaging algorithms (super-resolution, deconvolution, target phenomenology, low-SNR enhancement)
- Direct ML-based anomaly detection, behavior classification, and object discrimination frameworks
- Design multi-sensor fusion pipelines integrating GEOINT, Radar, RF, and optical data (Bayesian/ML methods)
- Lead trajectory estimation and 3D kinematic modeling (IOD, parallax, uncertainty quantification)
- Architect scalable scientific computing solutions (Python, C++, CUDA, HPC, cloud)
- Mentor junior engineers and help set technical road maps with client/mission leadership
Key requirements- 8+ years of experience in remote sensing, image or signal processing, or GEOINT data exploitation
- Experience with orbital mechanics, satellite characterization, domain-specific SDA workflows
- Experience with Python, scientific Python packages, or OOP languages (C++, JavaScript)
- Experience architecting with large-scale software environments (CUDA, HPC, cloud)
- Experience with ML systems for imagery processing (detection, tracking, classification)
- Experience with CI/CD pipelines (Kubernetes, Docker, Jenkins)
- Active TS/SCI clearance; willingness to take a polygraph
- Bachelor's degree in a STEM field
- collaboration across multidisciplinary teams
- mentorship and leadership
- effective communication with clients and mission leadership
- Python, scientific Python packages
- C++
- CUDA
