The University of Pennsylvania is looking to solve the problem of advancing computational research initiatives by developing cutting-edge software solutions and strong software engineering expertise.
Requirements
- Demonstrated experience in designing foundation models and conducting post-training workflows, including work with LLMs and VLMs.
- Proficiency in Python and its ecosystem of AI/ML frameworks and tools.
- Strong familiarity with HPC and AI computing environments.
- Experience in building agentic AI tools that integrate planning, tool use, and multi-step decision-making into end-to-end machine learning workflows
- Experience with cloud-based and on-premises environments
- Experience with software pipelines for real-time data processing
- Experience with complex database models for storing and disseminating scientific datasets
Responsibilities
- Contribute to cutting-edge research projects that require advanced software solutions and strong software engineering expertise
- Designing and post-training foundation models (including LLMs and VLMs) to support a wide range of academic research projects.
- Developing innovative methodologies for analyzing massive datasets in both cloud-based and on-premises environments, including experience in building agentic AI tools that integrate planning, tool use, and multi-step decision-making into end-to-end machine learning workflows
- Designing and implementing software pipelines for real-time data processing, and developing complex database models for storing and disseminating scientific datasets.
- Collaborating with faculty and researchers to advance computational research initiatives, enabling access to specialized software, tools, and datasets that support AI-intensive methods.
- Creating new software solutions or optimizing existing systems to align with best practices for quality, reusability, robustness, portability, and documentation.
- Partnering with research groups to develop AI/ML solutions using established artificial intelligence libraries.
Other
- Bachelor's degree in a quantitative discipline such as computer science, engineering, or bioinformatics, with a background in scientific computing and four or more years of professional experience in software development or equivalent combination of education and experience.
- Willingness to teach, mentor, and engage in continuous learning of emerging techniques.
- Proven ability to identify and select appropriate tools and technologies to ensure the successful execution of complex tasks.
- Master's or PhD in a quantitative discipline preferred.
- Five or more years of experience supporting AI and HPC code development.
