Associate AI Software Engineer (level 1)

Northrop Grumman Northrop Grumman · Aerospace · Dulles, VA +1 · Software

Associate AI Software Engineer (Level 1) at Northrop Grumman focused on Reinforcement Learning (RL) and Supervised Learning (SL) for space and aerospace programs. Responsibilities include novel algorithm R&D, prototyping in Python/JAX/PyTorch, porting to C++/CUDA, developing physics-based autonomy for mission planning, anomaly detection, and flight readiness testing. Requires an active Top Secret clearance and experience with ML/RL in a product line environment, coding from literature, and physics-based AI applications.

What you'd actually do

  1. Perform Novel Algorithm R&D
  2. Design and implement state-of-the-art RL / SL algorithms drawn from the latest literature
  3. Rapidly prototype in Python/JAX/PyTorch, then port to embedded C++/CUDA
  4. Develop Physics-Based Autonomy to perform Mission Planning & Decision-Making
  5. Apply supervised learning, reinforcement learning, and other AI/ML techniques to high-fidelity astrodynamics planning and controls problems, including real-time constraint handling

Skills

Required

  • Active U.S. Government Top-Secret clearance
  • Bachelor’s degree with a minimum of 1 year of relevant AI engineering experience (or 4+ years experience in lieu of degree)
  • Travel up to 25%
  • Foundational education of AI, with a focus on ML, RL, or SL model development
  • Machine learning usage in a product line environment
  • Hands-on coding of learning algorithms from primary literature
  • Physics-based AI application experience
  • Developing scalable RL/SL and other ML pipelines
  • Designing novel algorithms tailored to complex, real-world dynamics
  • Software engineering best practices and standards
  • Simulation development for space vehicle applications
  • Embedded Software, Space Flight Software, or Simulation Software experience
  • Python
  • CUDA
  • C/C++ programming

Nice to have

  • Current/Active TS/SCI
  • MS or PhD in Computer Science or Reinforcement Learning, or STEM degree field with strong physics-based numerical modeling and AI/ML experience
  • Diverse programming proficiency: C/C++, Python

What the JD emphasized

  • Requires an active U.S. Government Top-Secret clearance [TS] at time of application
  • Experience with hands-on coding of learning algorithms from primary literature—comfortable translating equations to optimized code
  • Experience with physics-based AI application (e.g. for spacecraft, robotics, autonomous aircraft, drones, rockets, or similar) in academia or industry
  • Experience in developing scalable RL/SL and other ML pipelines, with a track record of designing novel algorithms tailored to complex, real-world dynamics

Other signals

  • AI/ML
  • Reinforcement Learning
  • Autonomy
  • Spacecraft Operations
  • Algorithm R&D