Conduct research and develop machine learning models for finance, focusing on deep learning and large language models, optimizing them for performance, and collaborating with teams to integrate ML solutions.
Job Description
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.
Researchers build and deploy models across equities, options, fixed income, and derivatives domains, often working with petabyte-scale data.
Models incorporate advanced techniques: deep learning, sequence / time-series models, representation learning, and methods to tame overfitting and ensure robustness in financial regimes.
The goal: each model isn't a theoretical exercise - it has a measurable P&L impact (or reduces risk / cost) when deployed in live market-making or trading contexts.
Key Responsibilities:
• Conduct cutting-edge research and development in machine learning, with a focus on large language models (LLMs) and Deep learning and their applications in quantitative finance.
• Design, implement, and optimize machine learning models for performance and scalability, particularly in financial contexts.
• Collaborate with cross-functional teams to integrate ML solutions into business processes and trading strategies.
Skillset Requirements:
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 .
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.
Researchers build and deploy models across equities, options, fixed income, and derivatives domains, often working with petabyte-scale data.
Models incorporate advanced techniques: deep learning, sequence / time-series models, representation learning, and methods to tame overfitting and ensure robustness in financial regimes.
The goal: each model isn't a theoretical exercise - it has a measurable P&L impact (or reduces risk / cost) when deployed in live market-making or trading contexts.
Key Responsibilities:
• Conduct cutting-edge research and development in machine learning, with a focus on large language models (LLMs) and Deep learning and their applications in quantitative finance.
• Design, implement, and optimize machine learning models for performance and scalability, particularly in financial contexts.
• Collaborate with cross-functional teams to integrate ML solutions into business processes and trading strategies.
Skillset Requirements:
- Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems
- Deep knowledge of LLM architectures, including transformers.
- Familiarity with attention mechanisms, normalization techniques, and model architecture design.
- Training techniques (pre-training, fine-tuning, RLHF), and optimization methods.
- Understanding of low-level details like GPU memory management, precision types (float16, bfloat16), and parallelization techniques.
- Proficiency in advanced training techniques such as pre-training, fine-tuning, RLHF, and DPO.
- Expertise in Python and ML frameworks like PyTorch or TensorFlow.
- Familiarity with Retrieval Augmented Generation (RAG) systems and their implementation.
- Proven ability to approach open-ended problems and design end-to-end solutions in ML/AI.
- Strong mathematical and statistical foundations, particularly in areas relevant to quantitative finance.
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 .
Similar Jobs at Citadel Securities
Information Technology • Software • Financial Services • Quantitative Trading
Translate mathematical models into ultra-low latency implementations, optimize trading algorithms, and develop high-performance C++ systems for real-time trading.
Top Skills:
C++GpusTpus
Information Technology • Software • Financial Services • Quantitative Trading
As a PhD intern, you will develop and test trading strategies, perform statistical analysis, and collaborate with senior researchers.
Top Skills:
C++PythonR
Information Technology • Software • Financial Services • Quantitative Trading
Conduct research and develop automated trading strategies using advanced statistical techniques and programming skills. Collaborate in a fast-paced team to innovate and implement quantitative models.
Top Skills:
C++PythonR
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

