Currently tracking 12 active AI roles, with 2062 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $83k–$292k (avg $184k).
Northrop Grumman currently has 15 active job listings related to artificial intelligence. The company's hiring is concentrated in roles focused on agents and serving infrastructure, each representing 33% and 27% of the listings, respectively, with post-training roles also at 27%. Engineering is the primary function for these positions, with all roles located in the United States. Frequent technical tags include agent orchestration, evals, and model serving, suggesting a focus on the practical deployment and evaluation of AI systems. In the last 30 days, Northrop Grumman has posted 14 new AI roles, a significant increase from the previous 30-day period.
Northrop Grumman currently has 14 active AI-related roles in our index. The most common open titles are: AI Systems Engineer (Principal or Sr. Principal Level), Algorithm Software Engineer - Level 4, Engineer / Principal Systems Engineer - Prognostics / PHM, Machine Perception (MP) Engineer – Level 3 or 4, Principal / Sr Principal AI Software Engineer. Most positions are in Engineering.
Northrop Grumman's active AI hiring is concentrated in: data (50%), post-training (29%), serving infrastructure (21%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Northrop Grumman is hiring AI talent in: United States (14 roles).
Job postings at Northrop Grumman most frequently mention: C++, Software Engineering, Python, NumPy & Pandas, Machine Learning.
In the past 30 days, Northrop Grumman has posted 21 new AI-related roles. That is a +62% change versus the prior 30 days (13 → 21).
| Title | Stage | AI score |
|---|---|---|
| Principal Systems Algorithm Engineer Develops and evaluates novel EOIR sensor capabilities and algorithms, including sensor modeling, signal/image processing, and AI/ML algorithm development, for advanced EO/IR sensing in defense applications. Involves analyzing sensor data and generating synthetic data using physics-based models. | Data | 7 |
| Senior Principal Systems Algorithm Engineer Senior Principal Systems Algorithm Engineer at Northrop Grumman focused on advanced electro-optical and infrared (EO/IR) sensing. The role involves leading a team in sensor modeling, signal/image processing, and AI/ML algorithm development for emerging sensors and mission areas. Responsibilities include developing concepts for novel EO/IR sensors, creating cutting-edge algorithms, analyzing sensor data, and generating synthetic data using physics-based models. Requires experience with EOIR sensors, algorithm development, and team leadership, with a Secret clearance required. | DataPost-train | 7 |
| Software Engineer Level 5 Software Engineer to support algorithm development, testing, and evaluation of a new physics-based machine learning initiative for RF systems calibration. Requires C/C++, Python, Shell scripting, and experience with Digital Signal Processing algorithms. | Data | 7 |
| Software Engineer Level 4 Software Engineer to support algorithm development, testing, and evaluation of a new physics-based machine learning initiative for calibrating radio frequency (RF) systems using physical knowledge and large data sets. Requires C/C++, Python, Shell scripting, and Digital Signal Processing algorithms. | Data | 7 |
| Engineer / Principal Systems Engineer - Prognostics / PHM Engineer/Principal Systems Engineer for Prognostics/PHM at Northrop Grumman. Focuses on developing and implementing algorithms for predicting system health and failures using flight/sensor data, physics of failure models, and anomaly detection. Involves data analysis, requirement decomposition, and integration of inputs from multiple systems. Requires a STEM degree, experience in HM/PHM/R&M, data analysis, and anomaly detection, with a Secret clearance. | DataPost-train | 7 |
| Principal / Sr. Principal Data Scientist – Machine Learning and Predictive Analytics This role focuses on architecting and building custom, high-performance machine learning tools and data science solutions from the ground up, involving deep data modeling, pattern abstraction, and writing modular code. It emphasizes software engineering best practices within the data domain and tuning complex algorithms within on-premise infrastructure. The role requires a strong understanding of ML/DL, Python, SQL, and CI/CD. | Data | 7 |