The AI Lab operates as a small, agile team where practitioners are expected to move between research, development, and deployment activities. This position will contribute to strategy while doing hands-on technical work, building models, training systems, evaluating performance, and deploying solutions. The AI Lab collaborates closely with DCCA's Data Analytics and Risk and Surveillance sections, and coordinates with the Board's enterprise technology on infrastructure, governance, and compliance matters.
Responsibilities:
AI/ML and Generative AI Development
Deployment and Operations:
Collaboration, Communication and Agile Practices
Governance and Compliance Awareness
Required Qualifications:
At least six years of hands-on experience developing, deploying, and maintaining AI/ML applications within a large, professional, or academic organization
Bachelor's degree in Computer Science, Data Science, Statistics, Machine Learning, or related technology field (Master's degree preferred)
Expert proficiency in Python or R for data science development; experience with additional programming languages
Production deployment experience: Demonstrated ability to build, deploy, and maintain AI/ML applications in cloud environments, including containerization and basic CI/CD practices
Application development: Proficiency building interactive applications and dashboards using frameworks such as Streamlit, Dash, Flask, RShiny, or similar
Data visualization: Strong experience creating visualizations and dashboards using Python/R libraries, Tableau, Power BI, or similar tools to communicate technical concepts to non-technical audiences
AI/ML expertise: Advanced knowledge of machine learning, NLP (text normalization, Named Entity Recognition, POS tagging, word embeddings), and Generative AI technologies; experience with frameworks such as Scikit-learn, Spacy, XGBoost
Statistical analysis: Advanced knowledge of statistical modeling, data analysis techniques, and problem-solving skills
Ability to work independently and collaboratively, taking ownership of solutions from conception through production deployment
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