Principal AI Algorithm Development Engineers

RELOCATION ASSISTANCE:
Relocation assistance may be available

CLEARANCE TYPE:
None

TRAVEL:
Yes, 10% of the Time

Description

At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history - from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon.

We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history.

We're seeking AI researchers and engineers with deep knowledge of Computer Science and a deep focus on Physical AI to design and implement intelligent autonomy algorithms that will be applied to the space domain. In this role, the ideal candidate will:

Perform Novel Algorithm R&D

• Design and implement state-of-the-art RL / SL algorithms drawn from the latest literature in order to build, test, validate, and deploy Physical AI policies applied to the space domain.

• Rapidly prototype in Python/JAX/PyTorch, then port to embedded C++/CUDA.

Develop Physics-Based Autonomy to perform Mission Planning & Decision-Making

• Apply supervised learning, reinforcement learning, and other Physical AI/ML techniques to high-fidelity astrodynamics planning and controls problems, including real-time constraint handling.

• Fuse learned policies with classical GNC filters for robust guidance, navigation, and closed-loop control.

• Build models that re-optimize delta-V, power, and comm- (among other) constrained timelines using neural search or differentiable optimization.

• Develop AI solutions for real-time anomaly detection and response to ensuring robust and adaptive spacecraft operations. This includes developing models that detect out-of-family telemetry and select corrective actions via hierarchical or policy-gradient RL

• Lead Monte-Carlo, Processor-in-the-Loop, Hardware-in-the-Loop, and digital twin campaigns to prove safety and performance per internal standards.

This position can be filled as a Level 2 or 3.

Basic Qualifications:

Engineer

• Bachelor's Degree (in Computer Science, Reinforcement Learning, or in STEM) with 2 years of experience (or 1 year of experience [outside of internships/graduate research/etc.] w/ a Masters, or 1 year [outside of internships/graduate research/etc.] w/ a PhD). Experience can be considered in lieu of degree

• Strong physics-based numerical modeling and AI/ML experience

• Industry knowledge and/or foundational education of Physical AI and strong physics-based numerical modeling

• Proven track record of novel algorithm development (e.g., first-author papers, open-source releases, or production deployments)

• Hands-on coding of learning algorithms from primary literature—comfortable translating equations to optimized code

• Demonstrated physics-based AI application experience (e.g. for spacecraft, robotics, autonomous aircraft, drones, rockets, or similar) in academia or industry

• Proven experience in developing scalable RL/SL and other ML pipelines, with a track record of designing novel algorithms tailored to complex, real-world dynamics.

• Software Engineering Skills:
  Proficiency in software engineering best practices and standards, with experience in simulation development for space vehicle applications. This includes demonstrated experience in Embedded Software, Space Flight Software, or Simulation Software

• Python, CUDA, C/C++ programming experience

• Strong interest in space, national security, and related mission areas

• U.S. citizen

Principal Engineer

• Bachelor's Degree (in Computer Science, Reinforcement Learning, or in STEM) with 5 years of experience (or 3 years of experience w/ a Masters, or 1 year [outside of internships/graduate research/etc.] w/ a PhD). Experience can be considered in lieu of degree

• Strong…