Job Description Role Overview At Citadel Securities, we are at a once-in-a-generation opportunity in the financial markets. Machine Learning Researchers on our Options team come from a wide range of industries and turn cutting-edge ideas and petabyte-scale data into bleeding edge models with direct trading impact. Our team of researchers iterate quickly, own decisions end-to-end, and operate with substantial autonomy, resources, and scope in a flat, no-bureaucracy environment. Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel, please share your details and we will contact you if there is a vacancy available. Responsibilities Own the full research lifecycle, from hypothesis, experiment design, model validation, risk/overfit controls, to deployment Conduct cutting-edge research and development in machine learning (e.g. LLMs) at scale with a focus on industry leading techniques and their applications in quantitative finance Ship models to production that move P&L in options markets—measured by clear, testable outcomes Prototype → test → iterate fast The resources and support to take great ideas from concept to trading in a very short space of time Discover alpha in high-dimensional data with deep learning, time-series, and representation learning Engineer scalable research pipelines from feature generation to distributed training and backtesting Develop trading intuition to translate insights into executable strategies Leverage large scale compute and data (petabytes; large budgets) to run ambitious experiments and push the frontier Skills and Preferred Qualifications A curiosity to learn about financial markets, and excitement to understand microstructure, options dynamics, and volatility regimes on the job Masters or PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field, with advanced training and a strong research track record working on machine learning problems Deep knowledge of cutting edge large scale models and their training and design Training techniques (pre-training, fine-tuning, RL, RLHF), and optimization methods A results-oriented track record of having taken ML ideas from theory to measurable impact Strong math fundamentals (linear algebra, probability, optimization) and mastery of regression/ML for large scale data Hands-on with modern machine learning (sequence models/transformers, representation learning, regularization, cross-validation, causal/robust inference) applied in practice Bias to action & problem-solving demonstrated ability and comfort around owning decisions, iterating quickly, and simplifying complex problems to impactful solutions Curiosity about markets and enthusiasm to learn microstructure, options dynamics, and volatility regimes on the job Fluency in Python (NumPy, PyTorch) and the ability to write clean, modular, performant code for large-scale experiments About Citadel Securities Citadel Securities is a technology-driven, next-generation global market maker. We provide institutional and retail investors with world-class liquidity, competitive pricing and seamless front-to-back execution in a broad array of financial products. Our teams of engineers, traders and researchers harness leading-edge quantitative research and the accelerating power of compute, machine learning and AI to power our analytics and tackle the market’s and our clients’ most critical challenges. Together, we are forging the future of capital markets. For more information, visit citadelsecurities.com.