Design, develop, train, and validate advanced AI and machine learning models to support mission-critical use cases for a federal client.
Evaluate and select appropriate machine learning techniques, algorithms, and neural network architectures including frameworks such as TensorFlow and PyTorch.
Perform end-to-end data lifecycle activities, ensuring data quality, integrity, and compliance with federal data management policies.
Deploy AI/ML models into production environments, integrating with existing systems, cloud platforms, and APIs.
Establish and maintain MLOps pipelines to support CI/CD, automated testing, and performance monitoring.
Monitor model performance over time, implement retraining strategies, and optimize models.
Identify, assess, and mitigate bias in datasets and model outputs.
Collaborate with cross-functional teams, including data engineers and software developers.
Document model development processes to support auditability and compliance.
Support security and compliance initiatives by aligning AI/ML solutions with frameworks such as NIST and FedRAMP.

US Citizenship with ability to obtain a Public Trust.
Bachelor’s degree or higher in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical discipline from an accredited institution.
8+ years of progressive experience designing, developing, and deploying machine learning or artificial intelligence solutions within enterprise or mission-driven environments.
Demonstrated experience with machine learning frameworks and tools such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
Hands-on experience with data preprocessing, feature engineering, and working with large, complex datasets in both structured and unstructured formats.
Proven experience deploying and operationalizing AI/ML models in production environments, including integration with cloud platforms (e.g., AWS, Azure, or GCP).
Experience implementing MLOps practices, including CI/CD pipelines, model monitoring, versioning, and lifecycle management.
Strong understanding of responsible AI practices, including bias detection, model explainability, and ethical AI considerations.
Familiarity with federal security and compliance frameworks (e.g., NIST, FedRAMP) and experience working within regulated environments is preferred.
Strong analytical, problem-solving, and communication skills, with the ability to effectively collaborate across technical and non-technical stakeholders.
Local to Ashburn, VA and available to work onsite as needed.

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AI Machine Learning Engineer

Key skills