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Jump Trading
Posted 82 days agoVerified live 1d ago

Campus AI Research Engineer - Deep Learning (Intern)

Brief overview

Chicago, ILIn-person
UndergradOr in progress
$300k/yrStated minimum
Sponsors visasStated in posting
Machine learningDeep learningLanguage modeling architecturesTransformersState space models (SSMs)PythonC++PyTorchJAXTensorFlowHigh performance computing (HPC)GPU performance optimizationCUDAROCmPragmatism

Job description

Summary

Jump Trading Group is committed to world class research and seeks a Campus AI Research Engineer - Deep Learning Intern to apply machine learning in financial markets. The role involves implementing research projects, optimizing ML systems, and collaborating with researchers to enhance financial modeling.

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

Skills

  • 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
  • Experience with GPU performance optimization (CUDA or ROCm)
  • Experience with end-to-end model development
  • Strong opinions on best practices in ML research, tooling, and/or infrastructure

Qualifications

Must Haves

  • 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

Nice to Haves

  • Experience with HPC and distributed large model training
  • Experience with GPU performance optimization (CUDA or ROCm)
  • Experience with end-to-end model development
  • Strong opinions on best practices in ML research, tooling, and/or infrastructure

Benefits

  • INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

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