Campus AI Research Engineer — Deep Learning

P2P; New York (NY); On-site; USD 270,000 - 330,000; Full time

Job summary

Jump Trading Group in the United States (New York) seeks research scientists to apply machine learning to state-of-the-art challenges in finance. You will lead end-to-end projects from concept to production, collaborating with researchers and quants to build flexible ML frameworks and improve models and tooling.

Proficiency in Python and/or C++, experience with PyTorch/JAX/TensorFlow, and exposure to HPC, GPUs, and low-latency systems is required.

Qualifications

• Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent.
• Strong ML background with exposure to modern deep learning or language modeling architectures (e.g. transformers).
• Proficient in Python and/or C++.
• Experience with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow.
• Intellectual curiosity, versatility, and originality with a pragmatic outlook.
• Ability to thrive in a collaborative, team-oriented environment.
• Ability to reason through quantitative problems and communicate with researchers.
• Reliable and predictable availability.

Responsibilities

• Apply state-of-the-art techniques to complex and challenging domains.
• Work closely with researchers and quants to build flexible ML frameworks for financial ML.
• Optimize training pipelines to utilize HPC resources efficiently.
• Integrate ML models into production systems where latency matters.
• Work across languages: C/C++/Python/CUDA and other low-level GPU languages.
• Build large-scale ML systems that are observable, performant, and flexible.
• Other duties as assigned or needed.

Skills

Python

C++

CUDA

PyTorch

JAX

TensorFlow

Transformers

HPC

Research publishing

Collaboration

Job description

Jump Trading Group in the United States (New York) seeks research scientists to apply machine learning to state-of-the-art challenges in finance. You will lead end-to-end projects from concept to production, collaborating with researchers and quants to build flexible ML frameworks and improve models and tooling.

Proficiency in Python and/or C++, experience with PyTorch/JAX/TensorFlow, and exposure to HPC, GPUs, and low-latency systems is required.