AI Research Internship

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

A 12–14-week AI research internship at XTY Labs in New York, focused on machine learning, optimization, generative AI, foundation models, distributed training, and quantitative trading applications.

Requirements

  • Pursuing an advanced degree, ideally a Ph.D., in computer science, electrical engineering, mathematics, or a related quantitative field, with at least one year remaining before graduation.
  • Proven ability to conduct original research, including publications in leading machine learning and AI venues.
  • Strong practical understanding of deep learning architectures, particularly transformers.
  • Knowledge of data science, optimization, and statistics.
  • Strong programming skills; Python is acceptable.
  • Expertise with foundation models, large language models, and multimodal frameworks is desirable.
  • Experience managing and analyzing large, unstructured, noisy datasets is desirable.
  • Hands-on time series forecasting knowledge is desirable.
  • No prior finance experience is required.

Responsibilities

  • Conduct original machine learning research and investigate novel methods.
  • Apply deep learning, natural language processing, time series analysis, control, optimization, and reinforcement learning.
  • Build and refine robust models, agents, and software prototypes.
  • Communicate research progress and findings verbally and in writing.
  • Collaborate with quantitative researchers and foster teamwork.

Benefits

  • Sign-on bonus for accommodation costs
  • Benefits similar to those provided to US permanent employees
  • Mentorship from a full-time researcher and the Research Director
  • Consideration for full-time research roles in New York or London

Hiring Process

Four stages: introductory conversation with recruitment; practical take-home AI modeling exercise; discussion with the Research Director; and a final one-hour interview with an XTX Quantitative Researcher or XTY full-time Researcher.