AI & DL Researcher Intern (2026 Research Internship Program)

Confirmed live in the last 24 hours

Rock Bund Capital

Shanghai, Singapore

On-site

Posted January 13, 2026

Job Description

Who We Are

Founded in 2019, Rock Bund Capital is a proprietary trading firm deeply committed to shaping the future of the cryptocurrency industry. We have an average daily trading volume exceeding $1 billion and peak daily trading volume reaching $5 billion. We process over 7 million transactions daily, trading more than 1,000 symbols across multiple CEx and DEx. Our CEx activity is primarily focused on top-tier platforms, where we hold the highest VIP status. In DeFi, we provide liquidity to more than 20 most popular protocols across different chains.

Our team combines expertise in traditional finance, quantitative research, and advanced engineering with a deep understanding of blockchain technology. This unique blend enables us to excel in trading across complex crypto markets, including both CeFi and DeFi, while providing capital and strategic guidance to projects that drive innovation and foster sustainable growth in the crypto industry.

About the Program

We are inviting exceptional Ph.D. and graduate students from top-tier universities to join our research team. This internship is designed for those eager to bridge the gap between cutting-edge academic research and real-world financial markets. You will leverage your technical skills to solve complex challenges in high-frequency trading.

As an AI Research Intern, you will focus on translating state-of-the-art theory into impactful trading solutions through two primary research directions:

Deep Learning & Representation Learning: Design and train DNN architectures to create robust embeddings for complex market data.
Alpha Generation & Strategy Optimization: Utilize AI to discover new alpha signals, enhance existing trading strategies, and drive the monetization of research into production.

Who You Are

Currently pursuing a Ph.D. or Master’s degree in CS, AI, Math, Statistics, or a related field at a top-tier university.
Proficient in deep learning frameworks, especially PyTorch or JAX.
Strong coding skills in Python are required. Proficiency in C++ is a plus.
Hands-on experience with Transformer architectures or Time-Series Foundation Models.
Ability to read, understand, and implement state-of-the-art papers from top conferences.
Agile problem-solver with a passion for financial technology.
Plus: A publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD) in relevant fields.