Principal / Sr. Principal AI Software Engineer

Northrop Grumman•Dulles, VA

1d•$137,800 - $258,100•Onsite

About The Position

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. This position is contingent upon contract award and the candidate verifying and/or obtaining final clearances and program access(es) within a reasonable period of time as determined by the company. Expand your horizons, advance your career, and contribute to a secure future for generations. Northrop Grumman’s Space Sector invites you to bring your pioneering spirit to our collaborative teams. As an AI Software Engineer – Level 3 or 4 supporting our Space team, this role will be based at our Dulles, VA, Colorado Springs, CO, or El Segundo, CA locations. On our team, you’ll be a linchpin in missions of paramount importance, defining the art of the possible from day one. We are looking for early to mid-career AI researchers and engineers with deep knowledge of Computer Science and a deep focus on Reinforcement Learning (RL) to design and implement intelligent autonomy algorithms for our space and aerospace programs. In this role, you will be developing systems for a variety of spacecraft using current technologies and others yet to come! We are seeking team members who have a thirst for knowledge, approach each day with optimism, and have a relentless drive to solve complex problems. Creativity and innovation are imperative for this role, because at Northrop Grumman, many of the problems we work on are impossible… until they’re not.

Requirements

Must have and maintain a U.S. Government DoD Top-Secret (TS) security clearance at the time of application and the ability to obtain Sensitive Compartmented Information (SCI)/Special Access Program (SAP) approval/access within a reasonable period of time. US citizenship is required.
Bachelor’s degree with a minimum of 5 years of relevant AI engineering experience (Level 3) OR Bachelor’s degree with a minimum of 8 years of relevant AI engineering experience (Level 4)
May consider an additional 4+ years of experience in lieu of a completed degree
Master’s degree with a minimum of 3 years of relevant AI engineering experience (Level 3) OR Master’s degree with a minimum of 6 years of relevant AI engineering experience (Level 4)
PhD with a minimum of 1 year of relevant AI engineering experience (Level 3) OR PhD with a minimum of 4 years of relevant AI engineering experience (Level 4)
Industry knowledge and/or foundational education of AI, with a focus on ML, RL, or SL model development
Experience with machine learning usage in a product line environment
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
Experience/proficiency in software engineering best practices and standards
Experience in simulation development for space vehicle applications
Experience in Embedded Software, Space Flight Software, or Simulation Software
Experience with Python, CUDA, C/C++ programming

Nice To Haves

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, MATLAB/Simulink, Windows/Linux scripting
Demonstrated systems engineering excellence in requirements analysis, modeling and simulation, verification and validation at subsystem and system level or Demonstrated vehicle development, mission systems integration, ground and flight test validation experience
Experience in successfully developing and integrating software and hardware solutions for space applications
Experience in system and subsystem specification development including verification methodologies
Experience implementing action plans based on metrics and/or root cause/corrective actions
Hands-on technical experience with spacecraft or satellite related systems
Proven experience working with technically diverse teams across multiple locations
Experience with Space Flight Software, Simulation Software

Responsibilities

Perform Novel Algorithm R&D
Design and implement state-of-the-art RL / SL algorithms drawn from the latest literature
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 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 Verification & Flight Readiness
Lead Monte-Carlo, Processor-in-the-Loop, Hardware-in-the-Loop, and digital twin campaigns to prove safety and performance via internal standards
Participate in the full life cycle of software development, including requirements development, modeling and design, application development, unit to CSCI testing, integration, formal system testing, release, installation, and maintenance