SAIL Software Engineer, Hariri Institute

This role is based in Boston and follows a hybrid work schedule. Applicants should be located within a reasonable commuting distance of Boston.

For full consideration, please apply by Monday, September 21st.

The Rafik B. Hariri Institute for Computing and Computational Science and Engineering (Hariri Institute) is a university-wide research center reporting to the VP for Research, which serves as the university's premiere interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with computational and data science research. Located in the University's Duan Family Center for Computing and Data Sciences, the Hariri Institute community consists of over 400 faculty affiliates, 50+ administrative and research staff, 200 graduate students, and over $26 million in annual research expenditure. The Software & Application Innovation Lab (SAIL) at the Hariri Institute is a professional research, software engineering, and consulting lab that acts as both a driver and a collaborative partner for computational and data-oriented research efforts across Boston University. 

The Software Engineer position bridges the gap between scientific hypothesis and robust software execution. Reporting to the Director, you will work directly with postdocs, graduate students, and the Principal Investigator(s) to design, build, and maintain data pipelines, custom software tools, and computational workflows. This role ensures the lab's research code is stable, scalable, reproducible, and ready for peer-reviewed publication.

Core Responsibilities:

Software Development & Engineering

• Translate complex mathematical models, scientific algorithms, and raw scripts (Python, R, MATLAB) into clean, modular, and well-documented software packages.
• Develop and maintain data processing pipelines, user interfaces, or visualization dashboards for lab datasets.

Data & Infrastructure Management

• Containerize applications (using Docker or Singularity) to ensure identical execution environments across local machines, high-performance computing (HPC) clusters, or cloud platforms.
• Manage large-scale research datasets, ensuring secure storage, version control, and compliance with institutional data management policies.

Research Collaboration & Support

• Partner with lab researchers to understand their computational roadblocks and engineer custom tooling to automate workflows.
• Optimize existing code for performance, speed, and memory usage to handle growing dataset sizes.

Sustainability & Open Science

• Implement professional software practices within the lab, including version control (Git), automated testing, and continuous integration (CI/CD).
• Package and document software to open-source standards, enabling external researchers to replicate the lab's findings.