Associate AI Software Engineer/ AI Software Engineer (AHT)
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. The Northrop Grumman C2 & Weapons Integration (CWI) Artificial Intelligence (AI) Center of Excellence in Beavercreek, Ohio is seeking an AI Software Engineer. This role supports research and development in areas including Large Language Models (LLMs), natural language processing (NLP), natural language understanding (NLU), natural language generation (NLG), AI‑based decision-making, sensor fusion, data fusion, computer vision, and image processing, with a focus on responsible and explainable AI.
Requirements
- Associate AI Software Engineer (Level 1): Bachelor’s degree in Computer Science or a related STEM field with 0 years of relevant experience; an additional 4 years of relevant experience may be considered in lieu of a degree.
- AI Software Engineer (Level 2): Bachelor’s degree in Computer Science or a related STEM field with 2 years of relevant experience, or master’s degree in Computer Science or a related STEM field with 0 years of relevant experience; an additional 4 years of relevant experience may be considered in lieu of a degree.
- Experience implementing and/or applying one or more AI models and algorithms (for example: LLMs, deep neural networks, genetic algorithms, embedding models, deep learning architectures).
- Experience developing systems using AI/ML frameworks and libraries such as PyTorch, TensorFlow, Keras, or Scikit‑learn.
- Experience across the ML pipeline, including: Working with novel or heterogeneous datasets, Data processing and preparation, Training and fine‑tuning ML systems, Modifying existing deep learning architectures and implementing models from architecture diagrams, Evaluating system performance using established and custom metrics and methods.
- Ability to perform rapid prototyping and proof‑of‑concept implementations.
- General familiarity with applied machine learning concepts, including multilayer perceptrons, convolutional neural networks (CNNs), recurrent architectures such as LSTMs, transformer models, supervised and unsupervised learning methods, reinforcement learning methods, and statistical or graphical models.
- General familiarity with computational and statistical learning theory.
- Experience with web application development frameworks such as Flask or FastAPI.
- Understanding of software engineering practices, including use of source control and basic software architecture concepts.
- Ability to obtain a U.S. Government TS/SCI security clearance with CI Poly
Nice To Haves
- Active TS/SCI clearance with CI Poly
- Experience with AWS or other commercial cloud computing platforms.
- Experience with microservice architectures and related practices, including containerization and container orchestration technologies.
- Familiarity with explainable AI, adversarial AI, active learning, and third‑wave AI approaches.
- Familiarity with DevOps, DevSecOps, and/or MLOps concepts and workflows.
- Familiarity with Linux-based operating systems.
- Experience working independently to plan and execute technical tasks.
- Hands-on experience with LLMs (e.g., prompt design/engineering, use of LLM development frameworks, fine‑tuning, or model quantization).
- Experience with modeling and simulation.
- Experience using vector databases and/or graph databases.
Responsibilities
- Define, develop, and deliver mathematical and statistical models and algorithms to address prediction, optimization, and classification problems.
- Apply machine learning algorithms to large structured and unstructured datasets for use cases such as autonomy, pattern recognition, target detection and tracking, recommendation and decision support systems, signals processing, and robotic systems.
- Design, develop, document, test, debug, and deploy AI/ML applications.
- Collaborate with cross‑functional teams to deploy AI/ML solutions in development and production environments.
- Prepare and present technical progress and results to internal and external stakeholders.
Benefits
- Relocation assistance may be available
- health insurance coverage
- life and disability insurance
- savings plan
- Company paid holidays and paid time off (PTO) for vacation and/or personal business
- overtime
- shift differential
- discretionary bonus
- Annual bonuses
- Long Term Incentives (for VP or Director positions)
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
