AI Research Intern

The Role

As an AI Research Intern, your mandate is to research and prototype foundation models, both transformer-based and graph-based, applied to OnePay's customer, transaction, and merchant data. You'll work on real modeling problems and build a working prototype that demonstrates the approach. This role will impact OnePay's vision by providing a remarkable customer experience, driving positive business outcomes, and improving operational efficiency. You will work closely with the product, engineering and applied science team(s) working across all business units. This role reports to the Head of AI/ML.

This role is responsible for

• Research, design, and train foundation models on OnePay's data, working with transformer and/or graph-based architectures.
• Run experiments, evaluate results rigorously, and turn promising findings into a working prototype.
• Opportunity to work in an extremely fast paced growing company
• Partner with Product, Engineering and Analytics teams to ensure we are providing a remarkable customer experience.
• Driving significant impact on the company’s bottom line.

You Bring

• Final-Year Graduate Student: You’re in the final year of a master’s or PhD program, expected to graduate in Fall 2027 or Spring 2028, majoring in Engineering or a related field.
• Deep Learning Fundamentals: You have a strong grasp of how neural networks work under the hood, including backpropagation, attention, embeddings, optimization, and training dynamics. You've implemented, trained, or fine-tuned models yourself through research, coursework, or personal projects, and you're comfortable working in PyTorch or an equivalent framework.
• Prior Experience: You've completed at least one previous internship in research, machine learning, or software engineering, or have built substantial personal or academic projects you're excited to talk through.
• Availability: This is a full-time, 8-week program running June 21 - August 13, 2027. You are available to work in our New York City office at least 3-4 days a week throughout.
• Proactive & Collaborative Attitude: You have an act-like-an-owner mentality, thrive in a fast-moving environment, and enjoy working with others to achieve collective goals.
• Critical Thinking & Problem-Solving Skills: You enjoy tackling complex challenges, analyzing problems, and developing solutions. Clear communication of ideas is one of your strengths.
• Organized & Detail-Oriented: You’re a keen listener with strong organizational skills, capable of managing multiple tasks efficiently.
• Excited to Learn & Grow: You are passionate about being part of a rapidly growing start-up and look forward to expanding your skills in a real-world setting.

Nice to Have

• Familiarity with transformer-based foundation model architectures, including pre-training, fine-tuning, inference, and the tradeoffs between approaches.
• Exposure to graph-based learning or graph foundation models, such as GNNs, message passing, or representation learning on graph-structured data.
• Coursework or projects involving Large Language Models or Generative AI.
• Research output in any of the above: publications, workshop papers, or open-source contributions.

What We Offer

• Early access to a high potential, high growth fintech
• Hands on experience building product ready to ship
• Beautiful NYC SoHo Office
• Professional development and team social outings

Program & Application Timeline

• Program runs June 21 - August 13, 2027 (8 weeks, full-time, in our NYC office)
• We review applications and conduct interviews on a rolling basis as they come in
• No offer decisions will be made until the application window closes - all candidates are evaluated together before final decisions go out
• We are targeting a finalized cohort by December 1, 2026
• If there are intern spots still available, we may reopen applications in Spring 2027

Work Authorization: OnePay will not sponsor applicants who need employment sponsored visas for this position. Future sponsorship will not be considered.

Our process varies by role. Most candidates go through

• AI-assisted initial screen
• Interview with Talent Partner
• Technical or Hiring Manager Interview
• Team Interview
• Executive Interview
• Offer!