Systems Engineer - Machine Learning

ABOUT THE TEAM

The Space Ground Systems Engineering team solves the mathematical, physical, and algorithmic problems at the core of next-generation missile defense and fire control systems. We tackle dynamic battle-management challenges: fusing real-time sensor streams into track data, optimizing weapon-target assignment under uncertainty, and feeding high-confidence fire-control schedules back to the warfighter.

ABOUT THE JOB

We are looking for a Systems Engineer - Machine Learning to join our rapidly growing team in Huntsville, AL or Colorado Springs, CO. In this role, you will be responsible for bridging systems engineering, applied physics, and mathematical and machine learning to solve complex missile defense problems. You will design track-fusion pipelines, build threat-assignment algorithms, and conduct deep sensitivity analyses across complex architectures. This will require proficiency in applied math, physics, and algorithm development using Python or C++, alongside an understanding of sensor data and battle management workflows. If you are someone who moves quickly, loves diving deep into the math behind the system, and can operate autonomously to deliver verified, defensible technical solutions, then this role is for you.

WHAT YOU’LL DO

• Machine Learning: Research, develop, and deploy complex machine learning models such as generative ai, reinforcement learning, deep neural networks, physics based neural models.
• Algorithm Design and Development: Formulate and solve complex physics problems using mathematical techniques.
  • Ex: Object detection, tracking, and discrimination. Weapon-Target Assignment (WTA), sensor allocation, and fire control scheduling.
• Sensor Fusion & Tracking: Work on the components of system architecture that ingest raw/processed sensor data, execute track fusion, and perform threat classification.
• Parametric & Sensitivity Analysis: Design, conduct, and defend rigorous trade studies, sensitivity analyses, and parametric evaluations to determine system boundaries and validate performance.
• Prototyping & Modeling: Rapidly translate mathematical equations into clean, functional code (Python / C++) to run non-customer-facing modeling, simulation, and algorithm verification.
• Mission Systems Architecture: Bridge the gap between low-level physics/threat intelligence inputs and high-level mission outputs.

REQUIRED QUALIFICATIONS

• Currently possesses and is able to maintain an active U.S. Secret security clearance
• Experience: 5+ years of relevant engineering experience
• Bachelor’s, Master’s, or Ph.D. in Aerospace Engineering, Applied Mathematics, Physics, Electrical Engineering, Machine Learning, Artificial Intelligence, or a related quantitative field.
• Core Foundation: Strong mastery of applied mathematics, physics, and programming.
• Algorithmic Programming: Proficiency in Python and/or C++, Pytorch (or TensorFlow), Coding GPU's, multi-agent reinforcement learning, mathematical modeling, experience implementing foundation models, and algorithm development (you don’t need to be an enterprise software engineer, but you must be able to write robust code to solve math problems).
  • Windows, Linux, MATLAB,
• Domain Knowledge: Exposure to missile defense concepts, radar/sensor processing, flight dynamics, TOM, threat intelligence, discrimination algorithms, sensor tracking algorithms, kill assessment, integrated algorithms into operational systems, or fire control systems (GMD, NGI, SM3, Aegis, IBCS, C2BMC, SBI)
  • Military or defense operations experience is a strong plus.
• Security Clearance: Active U.S. Secret clearance required

PREFERRED QUALIFICATIONS

• Top Secret / SCI eligible preferred.