Two Sigma is proud to be a Silver sponsor of ICLR 2019.

The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.

ICLR is one of the fastest growing artificial intelligence conferences in the world. If you are attending ICLR 2019, visit us at booth #413. We look forward to meeting you.


Quantitative Researcher in Machine Learning

As a Quantitative Machine Learning Researcher, you will use a rigorous scientific method to develop sophisticated trading models, apply machine learning to vast often esoteric datasets, and partner with engineers to test complex investment hypotheses.

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Research Scientist in AI

As a Research Scientist in AI, you will apply general machine learning and specifically deep learning techniques to many types of problems, but particularly those with large amounts of noisy data. As part of this team you’ll remain connected to the broader research community.

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Software Engineer in Machine Learning

As a Software Engineer in Machine Learning, you will help develop the next generation of our machine learning infrastructure. We’ve attracted engineers who possess special capabilities in a wide variety of domains in-cluding data transformation and visualization, performance optimization, cloud computing, and distributed systems.

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AlphaStudio Research Consultant

AlphaStudio is Two Sigma’s global platform for collaboration on research problems at the intersection of data science, technology and finance. We partner with top scientists, students and professionals around the world through paid, part-time, remote research opportunities.

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