Global Quantitative Strategies (GQS) | Machine Learning Researcher

Citadel; City of Rochester (NY); Hybrid; USD 300,000 - 350,000; Full time

Job summary

Citadel's Global Quantitative Strategies (GQS) seeks a Machine Learning Researcher to join its team working across New York and Singapore. You will develop and deploy models for multiple asset classes, applying deep learning, sequence modeling, large language models, and reinforcement learning to capture price formation and market dynamics.

You will collaborate with researchers, engineers, and traders to scale robust systems and advance quantitative strategies within a world-class environment.

Qualifications

• Advanced degree in CS, ML, math, statistics, engineering, physics, or related quantitative field.
• Proven ability to conduct innovative and impactful research solving real-world problems.
• Deep expertise in ML and DL, such as sequence modeling, LLMs, or RL.
• Experience with pre-training, fine-tuning, RL, or related optimization methods.
• Strong Python and ML frameworks like PyTorch or JAX.
• Strong mathematical and statistical foundations.
• Ability to design, implement, and optimize ML models for performance, scalability, and robustness.
• Interest in financial markets and applying ML to model price formation, market behavior, and risk.

Responsibilities

• Develop and deploy ML models for multiple asset classes.
• Explore advanced ML techniques to improve robustness and performance.

Skills

ML research

Deep learning

Sequence modeling

Large language models

Reinforcement learning

Pre-training

Fine-tuning

Python

PyTorch

JAX

Mathematics

Statistics

Finance interest

Model optimization

Education

Advanced degree in quantitative field

Tools

PyTorch

JAX

Python

Job description

About Global Quantitative Strategies (GQS)

GQS is the quantitative investment business of Citadel. Founded in 2012, GQS has grown rapidly to become one of Citadel's core investment strategies and one of the top quantitative investment teams in the world. Collaborative teams of researchers, engineers, and traders build robust systems that operate at scale and apply advanced quantitative and machine learning techniques to identify investment opportunities.

Machine Learning Researchers at GQS develop and deploy models across a variety of asset classes. Their work spans deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, reinforcement learning, and methods for improving robustness in complex financial regimes.

Location

New York, Singapore

Required Skills and Qualifications:

• Advanced degree in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Physics, or a related quantitative field
• Proven ability to conduct innovative and impactful research focused on solving real-world problems
• Deep expertise in machine learning and deep learning, such as sequence modeling, large language models, or reinforcement learning
• Experience with modern training techniques such as pre-training, fine-tuning, reinforcement learning, or related optimization methods
• Expertise in Python and machine learning frameworks such as PyTorch or JAX
• Strong mathematical and statistical foundations
• Ability to design, implement, and optimize machine learning models for performance, scalability, and robustness
• Demonstrated interest in financial markets and a drive to apply machine learning techniques to model price formation, market behavior, and risk

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In accordance with applicable law, the base salary range for this role is $300,000 to $350,000.

In addition, the employee who fills this role will be eligible to participate in a discretionary incentive compensation program, as well as a wide array of benefit programs, such as medical and life insurance, retirement and tax-free savings plans, and access to other healthcare programs.