AI/ML Compliance Engineer - NO LONGER ACCEPTING CANDIDATES

A dynamic and forward-thinking organization is seeking a AI/ML Compliance Engineer to join its innovation team. This role focuses on applying artificial intelligence and machine learning—especially natural language processing (NLP)—to streamline and automate compliance and governance processes. The ideal candidate will bridge cutting-edge AI techniques with risk management and regulatory frameworks, enabling smarter, faster, and more proactive compliance solutions.

Clearance Requirement:

U.S. Citizenship required. Must be able to pass a Public Trust background investigation.

Key Responsibilities:

Build and deploy NLP models to extract and map compliance requirements from regulatory and policy documentation.

Design and implement ML-driven continuous control assessment tools for real-time risk identification and mitigation.

Partner with GRC experts to translate regulatory obligations into machine-interpretable logic and workflows.

Collaborate with engineering teams to construct and optimize data pipelines for model training, testing, and deployment.

Conduct experiments to evaluate various ML techniques (e.g., classification, anomaly detection, named entity recognition) for compliance use cases.

Maintain comprehensive documentation on models, datasets, performance metrics, and validation protocols.

Track developments in AI/ML relevant to regulatory technology and recommend strategic applications.

Support internal efforts to develop reusable, scalable AI/ML components and toolkits for compliance automation.

Required Qualifications:

Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.

5+ years of hands-on experience in AI/ML engineering, including model development and deployment.

Strong expertise in NLP techniques such as text classification, NER, and document similarity.

Proficiency with Python and libraries/frameworks like TensorFlow, PyTorch, Hugging Face, and scikit-learn.

Familiarity with DevOps and MLOps practices.

Strong analytical thinking and problem-solving abilities.

Effective communicator with the ability to collaborate across technical and non-technical teams.

Preferred Qualifications:

Experience applying AI/ML to regulatory compliance, cybersecurity, or risk domains.

Understanding of frameworks such as NIST 800-53, FedRAMP, ISO 27001, or similar.

Experience with secure data handling and model validation in regulated environments.