Campus AI Research Engineer – Research Automation (Intern)

Summary

Jump Trading Group is committed to world class research, empowering exceptional talents in Mathematics, Physics, and Computer Science. They are seeking a Campus AI Research Engineer Intern to apply machine learning techniques to complex domains, collaborate with researchers, and optimize production systems.

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