Quant jobs / Jump Trading

Campus AI Research Engineer – Research Automation (Intern)

An internship at Jump focused on automating and accelerating ML research workflows. You work with researchers on tools and pipelines that cut experiment turnaround.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Automate repeatable steps in the research workflow
Build reusable ML frameworks with quants
Speed up training on HPC resources
Make research systems observable and flexible

What they ask for

Required

Strong ML publications or open-source AI work
Modern deep learning such as transformers
Python and/or C++
PyTorch, JAX or TensorFlow
Quantitative problem-solving

Preferred

HPC and distributed training
CUDA or ROCm optimisation
End-to-end model development

Education: Not stated; research-level ML background expected
Experience: Campus intern
Languages and tools: Python
C++
CUDA
PyTorch
JAX
TensorFlow

How to prepare

Build an experiment-tracking and config-driven training harness
Profile and speed up a slow training loop
Reproduce a deep learning paper end to end
Learn job scheduling on a compute cluster

What to study

The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Jump Trading’s site before applying: requirements, location and pay can change after we check them.

View the posting on Jump Trading’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Jump Trading and doesn’t handle applications.