Vantor is seeking to solve the problem of helping decision makers and operators navigate what’s happening now and shape what’s coming next in the field of spatial intelligence, specifically in the context of Intelligence, Surveillance, and Reconnaissance (ISR) study efforts.
Requirements
- 3+ years of experience in AI/ML engineering, with a significant focus on deep learning and neural networks, OR demonstrable hands-on experience leveraging AI/ML in a simulation or scientific computing context.
- Demonstrable hands-on experience with foundation models or equivalent advanced AI/ML techniques, including familiarity with Large Language Models (LLMs), generative models, and vision models.
- Proficiency in Python and relevant AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers) as well as scientific computing libraries.
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps principles for deploying and managing AI models.
- Ability to develop standalone engineering tools/scripts via Python and/or Excel.
- Working knowledge of the theory and applications of astrodynamics, remote sensing, spacecraft design, aerospace systems operations, and complex systems integration.
- Experience with the design, development, and software implementation of complex mathematical algorithms for both simulation and AI applications.
Responsibilities
- Perform high-fidelity modeling and simulation of space and airborne ISR systems (satellites, aircraft, sensors).
- Design, develop, and implement AI/ML systems primarily focused on leveraging and customizing foundation models to enhance simulation analysis, data interpretation, and predictive capabilities.
- Fine-tune and adapt pre-trained foundation models for specific ISR tasks and domains, optimizing for performance, efficiency, and robustness within simulation contexts.
- Conduct research and experimentation with novel foundation model architectures, prompting techniques, and few-shot learning strategies to improve analysis outcomes.
- Instantiate complex operational vignettes, architect studies, and conduct trade-off analyses.
- Develop and integrate tools for data analysis, visualization, and AI model evaluation.
- Perform detailed Quality Assurance and Quality Control (QA/QC) checks of both simulation input/results and AI model outputs.
Other
- US Citizenship Required with an active or current TS/SCI clearance.
- Bachelors degree from an accredited college/university in Aerospace Engineering, Mechanical Engineering, Electrical Engineering, Mathematics, Physics, Computer Science, or a closely related quantitative field.
- Willingness to work on-site in the greater Northern Virginia/Washington, D.C./Maryland area.
- Strong interpersonal, written, and verbal communication skills.
- Ability to communicate complex technical concepts and establish collaborative relationships with both clients and teammates to achieve program goals.
