Machine Learning Researcher

Citadel Securities; Greater London; On-site; GBP 180,000 - 260,000; Full time

Job summary

Citadel Securities is seeking a Machine Learning Researcher for the Options team in London. You will own the full research lifecycle, from hypothesis and experiment design to validation, risk controls, and deployment.

The role focuses on cutting-edge ML methods at scale with direct trading impact. You will prototype and ship models that generate alpha from high-dimensional data, using deep learning, time-series, and scalable pipelines.

Qualifications

• Advanced degree in mathematics, statistics, physics, CS or related quantitative field.
• Strong track record in ML research with published work or significant project impact.
• Experience with large-scale models and training pipelines.

Responsibilities

• Own the full ML research lifecycle from hypothesis to deployment.
• Conduct cutting-edge ML research (LLMs) at scale for quantitative finance.
• Ship models to production with measurable P/L impact.
• Prototype, test and iterate rapidly with scalable compute and data resources.
• Develop alpha from high-dimensional data using deep learning and time-series.

Skills

Python programming

ML research

Transformers

Time-series modeling

Mathematics

Experiment design

Distributed training

RL/RLHF

Data analysis

Education

PhD in quantitative field

MSc in a quantitative discipline

Tools

PyTorch

NumPy

TensorFlow

Job description

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.

Location

London

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

Citadel Securities is the next-generation capital markets firm and a leading global market maker. We provide institutional and retail investors with the liquidity they need to trade a broad array of equity and fixed income products in any market condition. The brightest minds in finance, science and technology use powerful, advanced analytics to solve the market’s most critical challenges, turning big ideas into real-world outcomes.