Senior AI/ML Engineer

The Senior Artificial Intelligence (AI) / Machine Learning (ML) Engineer serves as the agency's senior technical data scientist providing mission critical analytics to detect and mitigate consumer product hazards. This position is located in the Directorate for Epidemiology (EP), Office of Risk Reduction (EXRR) at the U.S. Consumer Product Safety Commission (CPSC).

This position is officially titled Data Scientist (Artificial Intelligence). The working title is Senior AI/ML Engineer. The incumbent supports the modernization of CPSC's analytical ecosystem by designing and implementing AI/ML models, advanced analytical methods, cloud native workflows, and automation that accelerate hazard triage and strengthen data driven decision making across the agency. The Senior AI/ML Engineer performs the following duties: Designs, develops, tests, and deploys supervised, unsupervised, NLP, deep learning, and agent-enabled AI models that detect risks, surface signals, and identify leading indicators. Uses modern ML frameworks (e.g., PyTorch, TensorFlow) and scalable compute environments to build high-performance models that meet standards for accuracy, fairness, robustness, and transparency. Advises on high-quality data pipelines for ingestion, transformation, validation, quality enforcement, and preprocessing of diverse datasets. Operationalizes models in secure cloud environments (preferably Azure), leveraging cloud-native services, containerization, CI/CD automation, and scalable compute. Conducts analytical research to identify trends, patterns, and emerging hazards through statistical learning, causal inference, scenario modeling, and "what-if" simulations. Supports the agency's hazard detection research agenda by proposing new analytical methods, experimenting with novel architectures, and implementing advanced machine learning approaches. Acts as a key stakeholder with state-of-the-art knowledge in AI/ML, participating in working groups, communities of practice, and interagency collaborations. Works closely with program offices, engineering teams, compliance staff, field investigators, and agency leadership to translate analytic requirements into operational ML solutions. Communicates uncertainty, assumptions, limitations, and risk tradeoffs associated with modeling decisions and analytical findings. Designs and develops AI agents and retrieval-augmented systems (e.g., Copilot Studio, Python-based agents) that operationalize hazard detection workflows. Integrates AI agents with APIs, event streams, dashboards, and case management systems to reduce cycle time from signal to action. Performs other related duties as assigned.