Research AI Engineer

• Assists with the development, testing, and maintenance of basic AI models and related research software to support faculty-led research initiatives.
• Supports data collection, cleaning, preprocessing, and organization activities using established procedures and guidance from senior team members.
• Implements experiment tracking, and automated retraining following established protocols.
• Assimilates routine AI models into research infrastructure using containerization (Docker/Kubernetes) and cloud platforms (AWS Bedrock, Azure ML, or equivalent) following established procedures.
• Works within appropriate AI frameworks, tools, and architectures based on research requirements.
• Assists in preparing technical documentation, reports, and research materials for project records, publications, and presentations.
• Supports routine research activities including data collection, preprocessing, evaluation, and analysis.
• Troubleshoots routine technical issues in research software and AI workflows and escalates more complex problems to senior staff as appropriate.
• Following established procedures maintains and optimizes research software applications, APIs, and tools aligned with research software engineering best practices.
• Applies established software development practices, including version control, testing, code review participation, and documentation standards to ensure reproducibility and sustainability of research code bases.
• Identifies of routine design or performance problems and implements recommended solutions.
• Supports integration of research software, datasets, and AI models within university research computing environments and infrastructure using established procedures.
• Troubleshoots routine technical issues in research software and AI workflows and escalates more complex problems to senior staff as appropriate.
• Follows established guidelines to assist with evaluating and testing new AI tools, software, and technologies under the direction of supervisors and senior technical staff.
• Contributes routine technical information and project updates for research proposals, reports, and other administrative documentation as assigned.
• Maintains awareness of emerging developments in AI and research software engineering and participates in relevant learning and training opportunities.

Knowledge, Skills, and Abilities:

• Knowledge of cloud-based AI/ML platforms (AWS Bedrock, Azure ML, Google Vertex AI) and containerization tools (Docker, Kubernetes).
• Knowledge of Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, or equivalent).
• Strong written and verbal communication skills.
• Ability to translate complex technical concepts for various research audiences.
• Ability to work independently with moderate guidance and manage multiple concurrent research projects.