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# AI/ML Engineer

- **Company:** BAE Systems
- **Location:** Sterling, VA, United States
- **Experience:** Expert
- **Salary:** $149,603 - $254,317
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Big Data, Cloud Storage, Databases, Computer Engineering, Information Engineering, Extract Transform Load (ETL), Data Presentation, Data Systems, Data Visualization, Apache Hadoop, Monitoring of Systems, Data Intelligence, Machine Learning, Microsoft Office, Natural Language Processing, NLTK (NLP Analysis), Tensorflow, Prometheus, Software Engineering, Feature Engineering, Pytorch, Large Language Models, Grafana, Apache Spark, Deep Learning, Matplotlib, Scikit Learn, Information Technology, Modeling and Simulation, AWS Glue, Apache Kafka, Feature Selection, Spacy, New Relic (SaaS), Data Pipelines, Apache Beam
- **Published:** November 10, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9300419/aiml-engineer

## About the Role

* Bachelor's Degree in Computer Science, Data Engineering, Software Engineering, Computer Engineering or a related STEM field and 10 years work experience or equivalent experience
 * Understanding of the AI/ML development process, Large Language Models (LLMs), and their applications in AI.
 * Knowledge of AI/ML libraries and frameworks (e.g., TensorFlow, Pytorch, Scikit-learn).
 * Knowledge of data visualization tools (e.g., Matplotlib, Seaborn) and data storytelling techniques.
 * Familiarity with natural language processing (NLP) and computer vision libraries (e.g., NLTK, spaCy).
 * Experience with ETL/TS tools and frameworks (e.g., Apache Beam, AWS Glue).
 * Familiarity with big data technologies like Hadoop, Spark, and Kafka.
 * Strong communication skills with the ability to work across engineering disciplines
 * Excellent organizational and follow through skills.
 * Strong communication (written and verbal) skills.
 * Detail oriented with problem-solving skills.
 * Proficient in Microsoft Office

## Description

BAE Systems, a top ten prime contractor to the U.S. Department of War, enables the U.S. government to transform data into intelligence and provides engineering, integration and sustainment support for critical military platforms and systems. Intelligence & Security provides services and products to the Department of War, the intelligence community, federal law enforcement officials, and troops deployed around the world.

We are looking for an AI/ML Engineer to support the design, development, and deployment of intelligent systems that can learn from data, make predictions, classify objects, and generate insights supporting a new Enterprise lab environment across multiple classification levels. The lab supports new and emerging paradigms to support and enhance customer capabilities and tradecraft. The enterprise lab environment will encompass multi-intelligence data infusion to enable innovative tradecraft development modeling and simulation to provide solutions for customer problems and needs. Th AI/ML Engineer will develop high-quality analytic algorithms that drive business value and mission-critical use cases in support of an IC customer.

As the AI/ML Engineer you will:

 * Design, develop, and deploy AI/ML models using popular libraries and frameworks.
 * Conduct feature engineering and feature selection to optimize model performance.
 * Collaborate with Data Engineers to prepare data for AI/ML model development, ensuring that the data is in a suitable format for model training.
 * Implement AI/ML algorithms, including design, training, testing, verification, and validation activities.
 * Develop and implement data pipelines to enable retrieval of data from federated data systems (e.g., cloud storage or on-premises databases).
 * Develop and implement monitoring systems to ensure AI/ML model reliability and performance, using tools such as Prometheus, Grafana, or New Relic.
 * Stay up to date on best practices and emerging technologies in AI/ML, including advancements in deep learning, natural language processing, and computer vision.
 * Assess and provide recommendations on emerging intelligence methodologies and tools
 * Validate work against real and simulated data - making corrections for non-ideal data artifacts.
 * Brief internal stakeholders, internal subject matter experts, and potentially customers.
 * Build collaborative relationships with key leaders and peers, both internally and externally, across the organization.
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