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About the Role

Jump Trading Group is committed to world-class research, empowering exceptional talents in Mathematics, Physics, and Computer Science to push scientific boundaries and apply cutting-edge research to global financial markets. Our culture fosters innovation, fearlessness, creativity, intellectual honesty, and a competitive streak, believing in winning together and unlocking individual talent through collaboration and mutual respect. Research outcomes drive superior risk-adjusted returns, and we design, develop, and deploy technologies that change our world, fund start-ups, and partner with research organizations and universities to solve problems. We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal candidate will implement open-ended research projects from concept to production and continuously improve model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process, requiring a fluid mix of AI/ML expertise, engineering pragmatism, statistics, and market intuition.

Responsibilities

Apply state-of-the-art techniques to complex and challenging domains.
Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
Optimize training pipelines to make the best use of our HPC resources.
Integrate ML models into production systems where latency matters.
Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
Build large-scale ML systems that are observable, performant, and flexible.
Help improve productivity by reducing the iteration cycle time on research.
Other duties as assigned or needed.

Requirements

Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research.
Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs).
Solid development skills in Python and/or C++.
Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow.
Intellectual curiosity, versatility, and originality combined with a pragmatic outlook.
Ability to thrive in a collaborative, team-oriented environment.
Ability to reason through quantitative problems and communicate effectively with trading researchers.
Reliable and predictable availability.
Experience with HPC and distributed large model training (Bonus).
Experience with GPU performance optimization (CUDA or ROCm) (Bonus).
Experience with end-to-end model development (Bonus).
Strong opinions on best practices in ML research, tooling, and/or infrastructure (Bonus).
International students are encouraged to apply.
Accepts students eligible for CPT/OPT.
Sponsors work visas for full-time positions.

Skills

AI/ML
Engineering pragmatism
Statistics
Market intuition
Python
C++
CUDA
Deep learning techniques
Language modeling architectures
Transformers
SSMs
PyTorch
JAX
TensorFlow
HPC
Distributed large model training
GPU performance optimization
CUDA
ROCm
End-to-end model development

Work Type

Full-time

Salary/Compensations

$300,000 per year

About the Company

Jump Trading Group is committed to world class research.
Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak.
We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect.
At Jump, research outcomes drive more than superior risk adjusted returns.
We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges.
They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.