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# Sr. AI/ML Engineer

- **Company:** Meadowgate Technologies LLC
- **Location:** Herndon, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Computer Vision, Microsoft Azure, Cloud Computing, Cloud Engineering, Cyber Security, Computer Engineering, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Geospatial Intelligence, Graph Database, Apache Hadoop, Python (Programming Language), Machine Learning, Natural Language Processing, Rapid Prototyping Process, Tensorflow, SQL Databases, Systems Integration, Unstructured Data, Management of Software Versions, Google Cloud, Feature Engineering, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Model Validation, Cyber Threat Analysis, Agentic-AI, Data Lakes, Information Technology, Deployment Automation, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** October 26, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9263590/sr-aiml-engineer

## About the Role

5+ years working in artificial intelligence, machine learning, data science, or related software/data engineering disciplines.
Strong proficiency in Python and common AI/ML frameworks and libraries used for model development, training, evaluation, and deployment.
Demonstrated ability to develop machine-learning solutions for classification, predictive analytics, anomaly detection, computer vision, natural language processing, or similar applications.
Hands-on knowledge of the AI/ML lifecycle, including data preparation, feature engineering, model training, validation, testing, optimization, and deployment.
Ability to build and integrate data pipelines for ingesting, transforming, validating, and preparing structured and unstructured data.
Working knowledge of modern AI architectures and techniques, including LLMs, RAG, agentic AI, neural networks, and transformers.
Proficiency deploying AI/ML capabilities within cloud or enterprise environments and integrating models with applications, platforms, or mission systems.
Familiarity with MLOps practices such as model lifecycle management, monitoring, versioning, reproducibility, and automated deployment.
Ability to translate complex mission or technical requirements into scalable AI/ML solutions and communicate technical concepts to diverse audiences.
Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computer Engineering, Mathematics, Statistics, or a related technical field.
Active TS/SCI with a CI Poly.
Desired Skills:

Background supporting Intelligence Community (IC), DoD, national security, or other Federal Government missions.
Applied AI/ML knowledge within cybersecurity, GEOINT, threat intelligence, mission analytics, or related defense and intelligence use cases.
Familiarity with cloud-based AI/ML development using AWS, Azure, or Google Cloud Platform.
Knowledge of data engineering technologies such as ETL, data lakes/warehouses, SQL, Spark/Hadoop, Databricks, or graph databases.
Exposure to containerized AI/ML applications and scalable cloud or enterprise deployments.
Understanding of secure and responsible AI, AI governance, model risk, and security considerations for sensitive environments.
Background in AI/ML research and development, rapid prototyping, or transitioning emerging technologies into operational capabilities.
AI/ML, data science, cloud, cybersecurity, or related technical certifications., Proven ability to take AI/ML solutions from concept and prototype through development and operational implementation.
Ability to apply advanced analytics and AI techniques to complex, ambiguous mission or business problems.
Skilled at translating operational requirements into scalable architectures that integrate AI/ML with enterprise data, cloud platforms, and mission systems.
Ability to evaluate emerging technologies, develop proofs of concept, and identify practical applications for new AI capabilities.
Strong communication skills with the ability to work across engineering teams, mission stakeholders, customers, and senior leadership.
Understanding of the technical, operational, and security considerations associated with deploying AI/ML capabilities in defense or intelligence environments.