Machine Learning Engineer

Job Description
As a ML/Research Engineer at Citadel Securities, you will work closely with researchers to design and build the next generation library for deep learning within the firm. You will combine the best available open-source tools with deep internal expertise in modelling and predicting financial markets. Your work will empower 100+ researchers to iterate faster on their agenda and perform experiments that were not possible before.
Responsibilities:

• Grow/maintain internal library for deep learning.
• Work with researchers to understand their needs and add new functionality.
• Work with HPC experts to optimize the largest existing workflows and deliver training speed improvements and cost savings.
• Stay up to date with external innovations and tools and make them available for internal use as appropriate.

Qualifications:

• 5+ years of experience in machine learning and software development.
• Strong engineering skills, including Python, CUDA, C++.
• Experience building distributed deep learning libraries or scaling large distributed deep learning workflows using PyTorch (or similar).

About Citadel Securities:
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. For more information, visit CitadelSecurities.com .
About Citadel Securities
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.