Research Software Engineer II

Job responsibilities will include a subset of the following, depending upon the individual's background:

• Collaborate with our diverse team to help develop and improve large AI models, helping conduct experiments, analyze results, and co-author research publications.
• Develop, maintain, and improve our shared infrastructure for training/fine-tuning and prompting large AI models.
• Maintain software libraries/environment/Github repositories and support model use.
• Provide support for the use of these libraries within the core AI models group and for interdisciplinary work. This includes documenting projects in a descriptive, appropriately detailed manner that is understandable to both researchers and future Research Engineers.
• Serve as liaisons with Princeton High Performance Research Computing (HPRC) staff on GPU cluster-related issues.

We prioritize professional development for RSEs and offer the following opportunities:

• Learning the underlying science, mathematics, statistics, data analysis, and algorithms of computational research questions. This may involve conducting independent research, studying existing codebases, and staying up to date with publications.
• Building awareness of software development tools, techniques, software engineering best practices, programming languages, high-performance computing hardware, and computational research solutions.
• Access to a community of about two dozen research software engineers, as well as continued professional development opportunities at Princeton Research Computing.

• A minimum of 5 years as a Research Software Engineer or equivalent experience (e.g., graduate school, industry experience, open-source software development, etc.)
• A Bachelor's/Master's degree in computer science, engineering, sciences, or a related computational field is required.
• Solid coding skills and good experience with large AI models.
• Familiarity with GPU computing environments and ML frameworks and libraries (e.g., DeepSpeed, HuggingFace).
• Prior research experience in AI/ML and/or contributions to open-source libraries.
• Strong written and oral technical communication skills.

• Competitive compensation package with attractive work conditions.
• Access to state-of-the-art research facilities and GPU cluster.
• Opportunities for professional growth and career advancement.
• Collaborative and inclusive work environment that fosters creativity and innovation.

If you are passionate about advancing AI research, working alongside leading researchers, and contributing to impactful open-source projects, we encourage you to apply for this position. Applications will be accepted until all positions are filled.

Elevating the individual within a culture of collaboration, Princeton University provides a strong foundation for building one's career and family. Princeton's comprehensive benefits package reflects a holistic approach to supporting individuals and their families both at work and outside of it. The University is also an engaging, transformative resource in its own right. From opportunities for collaboration to world-class research and cultural facilities, you will find all kinds of spaces that bring people together and spark new ideas., The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.

If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.

The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. Standard Weekly Hours 36.25