Kempner Institute Undergraduate Summer Internship Program in ML Research Engineering 

Overview

The Undergraduate Summer Internship Program in ML Research Engineering at the Kempner Institute offers a structured opportunity for current undergraduates (interns) to further their experience in AI/ML engineering. The program is designed to provide college students with a hands-on learning experience supporting AI/ML research in an academic setting.

Interns will be mentored by a member of the Kempner Institute Research & Engineering Team and will work on a Kempner Institute research project directed by a Kempner Institute faculty member.   

Products resulting from the intern activities such as code, models, or datasets, may be published on Kempner Institute public channels, including GitHub, Hugging Face, or our Deeper Learning research blog.

Learning opportunities may include:

• Contributing to the development and improvement of innovative AI/ML/NeuroAI models and datasets. 
• Helping to optimize AI/ML/NeuroAI models to improve accuracy and computational efficiency, ensuring they are scalable and robust.
• Participating in the creation or optimization of LLMs, including developing evaluation benchmarks tailored to various tasks.
• Learning how to apply the best software engineering practices suited for AI and ML development.
• Designing and implementing AI workflows that run efficiently on AI HPC clusters.
• Enhancing the reproducibility of AI/ML workflows.
• Engaging with the open science community by helping to develop and disseminate open-source AI/ML scientific software packages.
• Gaining experience in multi-node distributed GPU training to enhance the performance of distributed AI/ML workflows. 
• Working on the numerical aspects of AI/ML algorithms to maximize efficiency and performance.
• Participating in data engineering tasks such as managing data warehouses, data lakes, and data processing pipelines.
• Developing skills in technical project management.

Requirements

The program is fully on-site, in person, at the Kempner Institute located at Harvard’s Science and Engineering Complex (SEC) at 150 Western Avenue, Allston, MA.  Remote work is not possible in this position.  

Applicants must be legally eligible to work in the United States. Visa sponsorship is not available for this position. 

Technical skills required:

• Proficiency in coding (Python) and deep learning frameworks (PyTorch) with a drive to enhance these skills.
• Familiarity with one of the AI/ML fields like natural language processing, computer vision, reinforcement learning, generative models, or a strong interest in exploring them.
• Basic data preprocessing, feature engineering, and model evaluation, or a strong willingness to gain hands-on experience.
• Eagerness to learn HPC concepts, including parallel computing, distributed systems, and optimization.
• Analytical skills, problem-solving abilities, and a growth mindset.

Basic qualifications:

• Applicants must be enrolled full-time in an undergraduate degree program or have earned a bachelor’s degree within the last year (i.e. after 5/1/2024). 
• The program requires a commitment of 35 hours per week. 
• The position starts June 16, 2025 and ends Friday August 22, 2025. An earlier start date may be available at the discretion of the program. 
• Students must be able to participate for the full 10 weeks of the program. 

How to apply

Applications will be accepted and reviewed on a rolling basis until all available positions are filled. The hiring committee will select applicants based on their qualifications as described in their application.  

To apply, please complete and submit the application form below.

Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.

Application process

Candidate applications are reviewed on a rolling basis. If selected, candidates will move through a two-step interview process conducted over Zoom. 

Light Technical Interview: This interview round assesses the applicant’s basic understanding of AI/ML research and engineering, and includes basic data structure and algorithm coding questions. If successful candidates will be invited to a final interview. 

Final Interview: Conducted with member/s of the Kempner Institute Research and Engineering Team, focusing on the applicant’s fit within the team and their potential contributions to the Kempner Institute projects.