We are seeking a Research Software Engineer (RSE) to contribute to the development and implementation of AI models, research frameworks, and computational tools with a goal to advance science. This role is ideal for individuals with a passion for AI research, strong programming skills, and a desire to work at the intersection of engineering and scientific discovery. The role will also provide teaching and training opportunities allowing the RSE to balance their time and focus between technical and professional development.
The RSE will be part of the recently established UD’s First State AI Institute (please check out the operational AI Center of Excellence https://sites.udel.edu/ai/ website to see some of the on-going activities) that aims to drive advancements in machine learning, deep learning, AI and data-driven intelligence. The Research Software Engineer will collaborate with interdisciplinary teams on campus to develop innovative AI solutions that have real-world impact.
The position includes benefits and competitive salary based on qualifications.
Responsibilities:
Software Development
Develop, optimize, and maintain software for AI research projects.
Collaborate with researchers to implement state-of-the-art machine learning models.
Work with large-scale datasets, designing efficient data processing pipelines.
Support the deployment and scaling of AI models for real-world applications.
Contribute to open-source AI projects and research publications.
Stay up to date with the latest advancements in AI and machine learning.
Be an advocate to maintain and improve computing infrastructure for code development
Create comprehensive documentation of any software developed
Complete user manuals for knowledge transfer, and ensure smooth handover with clear communication at the conclusion of the RSE software development
Qualifications:
Bachelor’s degree in Computer Science, Software Engineering, or a related field.
3+ years of Python experience with ML libraries (TensorFlow, PyTorch, scikit-learn), including optimization and deployment in production environments.
Strong grasp of AI/ML fundamentals including advanced concepts in model architectures, hyperparameter tuning, and real-world problem-solving
Proficiency in software development best practices (version control, testing, debugging), including CI/CD, containerization (Docker, Kubernetes), and robust debugging techniques.
Experience with cloud platforms (AWS, GCP, or Azure) and parallel computing, with a focus on cost-efficient and scalable model deployment.
Skilled in working with medium-large scale multicore and heterogeneous (CPU + GPU) clusters.
Excellent verbal and written communication skills.
Preferred qualifications
Master’s degree in a related field.
Experience with deep learning model training, evaluation, and distributed computing.
Contributions to AI research and open-source projects.
Strong collaboration skills across scientific disciplines.
Leadership or project management experience.
Ability to design and teach AI modules or training sessions.
Experience presenting research in publications, seminars, or conferences.