Responsibilities
- Investigate, architect, and construct AI and machine learning systems aligned with business goals.
- Develop experimental AI models and transition viable prototypes into operational platforms.
- Create software solutions using Large Language Models for tasks such as document summarization, classification, workflow automation, and data extraction.
- Refine prompt engineering methods and implement Retrieval-Augmented Generation (RAG) frameworks.
- Assess, adapt, fine-tune, and verify AI models to enhance precision and organizational impact.
- Employ advanced statistical and machine learning approaches, including supervised and unsupervised learning, regression and classification, deep learning, and natural language processing.
- Construct, release, and manage AI/ML applications in both cloud and local infrastructure.
- Build interactive analytical tools and dashboards using Streamlit, Dash, Flask, or R Shiny.
- Design clear data visualizations and interfaces with Tableau, Power BI, Plotly, Matplotlib, Seaborn, or ggplot2.
- Set up CI/CD workflows, containerization, and automated deployment using Docker and related tools.
- Implement monitoring, logging, alerting, model performance evaluation, and automatic retraining systems.
- Optimize generative AI implementations, including API governance, rate controls, and cost management.
- Diagnose and resolve technical and infrastructure problems while maintaining system reliability and scalability.
- Ensure deployed systems meet security, privacy, compliance, and governance standards.
- Engage in Agile processes such as sprint planning, daily standups, and retrospectives.
- Work directly with economists, analysts, legal experts, technical teams, and executives.
- Convert business needs into robust AI and data science implementations.
- Explain technical concepts clearly to both technical and non-technical stakeholders.
- Produce technical documentation, knowledge transfer materials, reports, and executive summaries.
- Guide team members and strengthen internal AI/ML expertise and best practices.
- Support adherence to federal regulations including FISMA, privacy policies, and records management.
- Coordinate with security, privacy, compliance, and IT teams on system integration.
- Apply principles of Responsible AI such as fairness, transparency, explainability, accountability, and bias reduction.
- Help prepare security documentation, privacy impact assessments, and Authority to Operate (ATO) submissions.
Work Arrangement
Remote (Worldwide)
