AI Lab - Research

The AI Lab is a research-focused trading team exploring how advances in machine learning can be applied to complex problems in quantitative research and trading. The Lab develops and runs its own ML-driven trading strategies, owning the full lifecycle from research and experimentation through production and revenue generation. The AI Lab sits within the Quantitative Strategy Group (QSG), and brings together researchers/traders, machine learning engineers, and software engineers to develop and execute its strategies.

As a Researcher in the AI Lab, your key responsibilities include:

Designing, developing, and training novel ML models and methods — including LLMs and other foundation models — drawing on advances in deep learning and sequence modeling, for deployment in production trading systems

Researching and developing new ML approaches for complex quantitative and sequential modeling problems

Formulating hypotheses and designing rigorous experiments and evaluation frameworks, using appropriate baselines, ablations, and out-of-sample testing to identify promising research directions and understand why approaches succeed or fail

Translating ideas from research papers and theoretical work into working implementations, adapting and extending them to new problem domains

Applying ML techniques to large-scale financial datasets, including time-series and unstructured data, to identify and evaluate potential predictive signals

Training and evaluating models at scale, leveraging GPU and distributed computing environments as needed

Building and leveraging research tooling, including agentic and automated research workflows, to accelerate experimentation

You’ll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets.

In addition, you’ll receive:

The opportunity to work alongside best-in-class professionals from over 40 different countries

401(k) match up to 50%

Comprehensive health, mental, dental, vision, disability, and life coverage

Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sports leagues and more

Strong foundations in machine learning, statistics, optimization, and experimental design.

Demonstrated ability to conduct independent ML research, from developing hypotheses through implementation, experimentation, and evaluation.

Deep understanding of modern deep learning architectures, particularly transformers, foundation models, sequence models, and/or state-space models.

Experience developing and training models rather than primarily applying or integrating existing models.

Strong empirical judgment and the ability to understand why an approach is or is not working and determine the next research direction.

Strong programming skills, particularly Python, with experience in frameworks such as PyTorch or JAX.

Experience training and evaluating models in GPU-based computing environments.

Experience in one or more of the following would be especially valuable:

Developing and training large-scale foundation models or LLMs

Large-scale sequence or time-series modeling

Transformers, efficient attention, SSMs, Mamba, RWKV, or related architectures

Reinforcement learning or sequential decision-making

Self-supervised, representation, or generative learning

Distributed training and large-scale GPU workloads

Quantitative research, financial markets, or high-frequency data

CUDA, Triton, custom kernels, or ML performance optimization

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