Research Software Engineer

University Overview

The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn’s distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America’s Best Large Employers in 2023.

Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.

The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.

Posted Job Title

Research Software Engineer

Job Profile Title

Application Architect

Job Description Summary

The University of Pennsylvania’s PennAI initiative and the Penn Advanced Research Computing Center (PARCC) core facility are seeking highly qualified and motivated Research Software Engineer (RSE) to join our team. In this position, you will play a key role in advancing scientific computing through the application of AI methodologies and sophisticated analytical tools, supporting the integration of these technologies within the academic research environment. Research Software Engineers (RSEs) will engage in interdisciplinary collaborations across computing, AI, data science, and related domains, contributing significantly to the university’s research mission.

Job Description

Job 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.
• Working closely with cross-functional teams—including researchers, data scientists, and software developers—to foster a culture of continuous learning and technical excellence.
• Partnering with research groups to develop AI/ML solutions using established artificial intelligence libraries.

Qualifications

• 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.
• 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.

Preferred Qualifications:

• Master's or PhD in a quantit