Northrop Grumman Aeronautics Systems is looking to add a Principal / Sr Principal Systems Engineer - Operations Analysis AI to join our team in El Segundo, CA. The candidate should be a self-starter with familiarity working in an Integrated Product Team (IPT) construct.
The selected candidate will perform operational‑analysis studies with a focus on mission data‑flow aggregation, dissemination, and architecture. This individual will be a subject‑matter expert (SME) in mission‑relevant data, its implementation across the enterprise, or the development of AI/ML solutions that accelerate data‑driven decision making in multi‑domain simulation environments.
Roles and Responsibilities:
- Model operational environments and conduct trade‑studies via computer simulation.
- Perform operational and effectiveness analysis to quantify capability gaps.
- Create and apply knowledge of Tactics, Techniques, and Procedures (TTPs) to support blue/red kill‑chains across multiple security environments, programs, architectures, and platforms.
- Provide blue/red tactics and CONOPS modeling, simulation, and analysis in mission‑level models to help achieve long‑term program objectives.
- Conduct mission‑engineering activities that ensure operational capabilities match delivered system performance through the Systems‑Engineering “V”.
- Develop, train, and validate AI/ML models (e.g., supervised, unsupervised, reinforcement‑learning, Bayesian) that:
- Analyze large‑scale data streams for pattern detection, anomaly identification, and predictive insight.
- Perform data‑compression (e.g., autoencoders, sparse coding, learned codecs) to reduce bandwidth/storage while preserving decision‑critical information.
- Supply real‑time decision‑support scores for complex, multi‑domain simulations.
- Automate and accelerate time‑intensive data‑workflow steps such as feature extraction, data‑fusion, and report generation.
- Design and implement MLOps pipelines (e.g., MLflow, Kubeflow, DVC) that integrate training, validation, versioning, and deployment into existing simulation and analysis toolchains.
- Leverage high‑performance computing (HPC) and GPU acceleration (CUDA, cuDNN, ROCm) to scale model training and inference for massive data sets.
- Synthesize stakeholder input, visualize results, and communicate findings to leadership at all levels.
There is no remote / hybrid / telework available for this position. Travel up to 25% may be required.
Basic Qualifications:
At the Principal Level:
- Must have a Bachelors Degree in a STEM field and at least 5 years of relevant military / professional experience, OR a Master's Degree in a STEM field and at least 3 years of relevant military / professional experience, OR a PhD and at least 1 year of relevant military / professional / academic experience
At the Senior Principal Level:
- Must have a Bachelors degree in a STEM field and at least 8 years of relevant military / professional experience, OR a Master's Degree in a STEM field and at least 6 years of relevant military / professional experience, OR a PhD and at least 4 years of relevant military / professional experience.
At Both Levels:
- Experience with coding in MATLAB or Python which includes AI/ML libraries such as TensorFlow, PyTorch, scikit‑learn, XGBoost, and SciPy.
- Experience in at least one of the following domains:
- Research, analysis, and assessment threats to U.S. military operations
- Vehicle performance analysis
- Navigation / Position Navigation & Timing (PNT)
- Survivability, lethality, vulnerability, engagement, or mission‑level analysis
- Electronic Attack (EA), Electronic Protection (EP), Electronic Countermeasures
- Red or blue CONOPS and TTPs
- Data‑science fundamentals experience: data preprocessing, feature engineering, statistical analysis, and model evaluation.
- Active DoD Secret clearance (with a background investigation within the past 5 years or enrolled into Continuous Evaluation) and ability to obtain and maintain Top Secret Clearance (TS).
- Ability to obtain and maintain initial and upgraded Special Access Program (SAP) access via Program Access Request process.
Preferred Qualifications:
- Current applicable SAP.
- Active DoD TS with SCI.
- Strong communication, interpersonal, and leadership skills, including project/analysis‑lead experience.
- Physics‑based modeling and simulation using object‑oriented programming (C++, C#, Java, or Python).
- Demonstrated ability to work in a rapid‑prototyping AI/ML environment.
- Experience with system‑of‑systems modeling tools (AFSIM, Suppressor, Brawler) and associated integration of AI/ML components.
- Familiarity with AGILE, MBSE, and system architecture frameworks; ability to embed data‑centric AI/ML deliverables into model‑based development cycles.
- Operational military background or experience providing insight into realistic mission constraints.
- Proficiency with version‑control systems and collaborative workflow tools.
- GPU/parallel programming experience (CUDA, OpenCL, MPI, Dask, Spark) for scaling model training and inference.
- Hands‑on experience building MLOps pipelines (MLflow, Kubeflow, Airflow, CI/CD for model deployment).
- Knowledge of explainable AI (XAI) techniques and model interpretability tools (SHAP, LIME, Saliency Maps) to support transparent decision making.
- Experience with data compression and representation learning (autoencoders, variational autoencoders, transformer‑based codecs) applied to telemetry and sensor streams.
- Prior work on workflow automation (Python scripting, PowerShell, Bash, RPA tools) that reduces manual data‑processing time.
- Experience modeling and simulating radars, missiles, integrated air‑defense systems (IADS), air and/or space platforms with AI‑enhanced assessment modules.
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