Citadel Securities

Deep Learning ML Researcher

Reposted An Hour Ago

Miami FL USA

In-Office

Entry level

Information Technology • Software • Financial Services • Quantitative Trading

We embrace bold ideas and seize opportunities others don’t from the way we operate to the strategies we deploy.

The Role

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.

Summary Generated by Built In

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:

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 .

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The Company

HQ: Miami FL

1900 Employees

Year Founded: 2002

What We Do

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.

Why Work With Us

We do not accept the status quo and we are constantly looking to achieve what others think is impossible. That’s true not just in our careers but also in our communities.