Research Software Engineer II

Responsibilities

• Initiate and maintain open collaboration with researchers across Princeton University.
• Regularly meet with, listen to, and ask questions of researchers to ensure the engineered solutions fit the research need.
• Apply AI and machine learning algorithms to software engineering projects in the researcher’s specific domain.
• Research Software Engineering: Work independently with minimal guidance to understand and translate research priorities into flexible software solutions.
• Collaborate with a team to develop comprehensive open source software solutions and models based on researcher-provided requirements and desired outcomes.
• Conduct independent or team research to identify and solve problems, and provide detailed documentation for the research team.
• Contribute to software solutions by establishing project-specific best practices, including version control, continuous integration and delivery, software design, and programming models.
• Ensure long-term maintainability, sustainability and open access by thoroughly documenting projects.
• Provide support for the use of software libraries, including detailed documentation that is accessible to both researchers and future Research Software Engineers.
• Contribute to improving the performance and quality of new and existing code bases through hands-on work with ongoing research.
• Serve as a liaison with Princeton Research Computing staff on GPU cluster-related issues.

Qualifications

• Bachelor’s degree or equivalent in computer science, engineering, applied math, sciences, or related computational field.
• A minimum of 4 years as a Research Software Engineer or equivalent experience (e.g. graduate school, industry experience, open-source software development, etc.).
• Proficiency in programming languages used in AI and computational research (e.g. Python, C++, R, MATLAB, Julia).
• Expertise in machine learning algorithms and techniques.
• Familiarity with AI frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Experience working with large datasets and familiarity with GPU computing environments.
• Demonstrated success: Consistently using conventional and readable coding style. Creating comprehensive and well-written documentation. Using version control systems.
• Demonstrated successes contributing to a collaborative research team.
• Ability to work independently.
• Strong written and oral technical communication skills with the ability to present complex research findings to technical and non-technical audiences.

Preferred Qualifications

• Expertise in conducting research in Artificial Intelligence and Machine Learning.
• Contributions to open-source libraries and publications in relevant journals or conferences are highly valued.
• Experience participating in multiple software development projects simultaneously, ensuring timely delivery and adherence to quality standards.
• An eagerness to take on more responsibility and develop project management skills.
• Masters/Ph.D. in computer science, applied science, or other related field with a strong computational focus or equivalent experience in a research setting preferred.