AI Lab - Research

Optiver • New York, NY

5d • Onsite

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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
• Pre-training, post-training, or novel model architecture research
• Distributed training and large-scale GPU workloads
• Quantitative research, financial markets, or high-frequency data
• CUDA, Triton, custom kernels, or ML performance optimization
• Agent-assisted or automated research methodologies

Responsibilities

• 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

Benefits

• 401(k) match up to 50%
• Comprehensive health, mental, dental, vision, disability, and life coverage
• 25 paid vacation days alongside market holidays
• Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sports leagues and more

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed