Position Title: Aerospace Engineer
Position Type: Full-time (ON-SITE)
Position Location: Chantilly, VA
Clearance Required: TS/SCI w/CI Poly
Waypoint's client is seeking a highly motivated and skilled Aerospace Engineer to join their team supporting a critical government client. This position offers the opportunity to support RDT&E for cutting-edge projects supporting space-based systems.
Responsibilities:
- Develop and maintain physics-based simulation models of spacecraft systems, including structures, sensors, and mission environments.
- Perform end-to-end performance modeling for satellite missions, integrating sensor, orbital, and environmental models.
- Conduct sensor phenomenology studies, including optical, infrared, or radar modeling for detection, tracking, and signature analysis.
- Perform orbital mechanics modeling including orbit determination, orbital maneuvering, and spacecraft flight dynamics
- Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis, and interface between simulation tools.
Required Qualifications:
- Bachelor’s or Master’s degree in Aerospace Engineering, Mechanical Engineering, Physics, or a related field.
- 3+ years of experience in modeling and simulation for aerospace or space systems.
- Active Top Secret/SCI w/Poly Clearance
- Strong understanding of sensor phenomenology—such as optical, infrared, or radar systems—and associated modeling methods.
- Intermediate Python programming experience, demonstrated through hands-on experience with tasks such as data manipulation, automation, and development of Python-based solutions. Experience with libraries such as NumPy, SciPy, pandas, and matplotlib is beneficial.
- Ability to communicate technical results clearly in both written and verbal formats.
Preferred Qualifications:
- Master's degree in a STEM related field.
- 6+ years of related experience.
- Experience with other simulation tools and programming languages.
- Experience with non-cooperative target tracking.
- Experience with collection & revisit modeling.
- Knowledge of cloud computing platforms (e.g., AWS, Azure).