AI/ML Engineer

As an Al/ML Engineer in CPSC's Analytics Center of Excellence, you advance the agency's mission by developing Al-enabled capabilities that accelerate all elements of CPSC’s mission from risk detection, to enforcing regulations, and all manners of decision-making. You collaborate with program offices, support cloud native modernization, and provide insight on various highly technical Al/ML projects while balancing long term data strategy with rapid response needs.

Qualifications:

In addition to the mandatory education requirement, all applicants must have 52 weeks of specialized experience equivalent to at least the next lower grade level in the Federal Service. Specialized experience is experience that has equipped the candidate with the particular knowledge, skills, and abilities to perform successfully the duties of the position.

Qualifying specialized experience must demonstrate the following:  

GS-11: 1) Assisting with machine‑learning workflows, including data preparation, model training, and evaluation; 2) using Python and SQL to analyze structured/unstructured data and supporting NLP or deep‑learning tasks; 3) contributing to cloud‑based AI/ML work, basic MLOps practices and preparing technical summaries for diverse audiences; and 4) collaborating within project teams to support the development and deployment of analytical or AI/ML solutions. 

GS-12: 1) Independently designing and deploying end‑to‑end machine‑learning models, including feature engineering, model optimization, and production implementation; 2) applying advanced AI/ML methods (NLP, deep learning, anomaly detection, generative models) and implementing MLOps practices such as CI/CD, monitoring, and drift detection in cloud environments; 3) applying data‑governance or AI‑risk‑management standards and preparing technical documentation that informs program decisions; and 4) serving as a technical project lead to guide the adoption of AI/ML practices.

Evidence of the above specialized experience must be supported by detailed documentation of duties performed in positions held.  Your resume is the key means we have for evaluating your skills, knowledge, and abilities as they relate to this position. Therefore, we encourage you to be clear and specific when describing your experience. We will not make assumptions regarding your experience or based on job titles alone.  If your resume does not support your questionnaire answers, we will not allow credit for your response(s).

Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

Applicants must meet the qualifications for this position by the closing date of this announcement.

Responsibilities:

This position is officially titled Data Scientist (Artificial Intelligence). The working title is AI/ML Engineer.

The Artificial Intelligence (AI) / Machine Learning (ML) Engineer will design and implement advanced technical solutions [e.g., natural language processing (NLP) models, agent-native and open-source generative pre-trained transformers (GPTs), multi-agent orchestration, etc.] focused on extracting actionable insights, evaluating model performance, and enhancing product safety decision-making. This role emphasizes data quality, performance, and interoperability in modern cloud environments, enabling CPSC’s strategic acceleration toward preventative analytics for product safety. This role requires collaboration with data engineers, statisticians, program analysts, IT specialists, and more.

The AI/ML Engineer is responsible for:

• Helping to build and maintain machine learning pipelines — from pulling in new data to training, testing, and deploying models — using modern cloud‑based tools and engineering practices.
• Monitor how models perform over time, watching for issues like data drift or drops in accuracy, and help improve them so they are reliable, efficient, and cost‑effective. Contribute to automating ML workflows using CI/CD and MLOps practices.
• Build and integrate AI agents using tools such as Copilot Studio, Python‑based agents, or retrieval pipelines to speed up analytics workflows and help the agency make faster, better‑informed safety decisions.
• Support the selection, training, and tuning of machine learning models — including models for prediction, anomaly detection, and natural language processing — ensuring they are accurate, fair, and scalable.
• Use deep learning frameworks like PyTorch and TensorFlow to work with both structured and unstructured data, helping ensure the models you develop meet quality standards for transparency and performance.
• Prepare clear technical documentation, summaries of model performance, and other materials that explain your work. Communicate complex AI/ML concepts in a way that non‑technical audiences can understand.
• Participate as a member of an Agile, cross‑functional team—collaborating with data engineers, analysts, program staff, and IT partners to deliver iterative improvements and solve problems together.
• Serve as a technical resource for data science principles, helping develop integrated “data fusion” products and staying current on emerging AI/ML methods through ongoing learning and collaboration.
• Take part in AI/ML working groups and communities of practice across the agency and federal space. 

This vacancy announcement will close after the receipt of the first 100 applications.

Salary : $85,447