Quant jobs / G-Research

Machine Learning Engineer Internship

A 12-week summer internship in G-Research's Technical Machine Learning team, working alongside quant researchers. It is engineering-heavy, focused on making ML training faster and more scalable.

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.

Implement ideas from published ML papers
Write custom libraries to train models efficiently on very large data
Profile model architectures to find performance bottlenecks
Evaluate new ML hardware and software

What they ask for

Required

Current undergraduate, master's or PhD student in ML or similar
Object-oriented programming
Python, PyTorch and NumPy
Strong ML reasoning
Teamwork and communication

Preferred

Optimisation methods
HPC
Profiling
Model inference

Education: Current undergraduate, master's or PhD student in machine learning or related
Experience: Students; finance experience not necessary
Languages and tools: Python

How to prepare

Implement a transformer or similar model in PyTorch and profile where the time goes
Learn GPU basics and mixed-precision training
Reproduce a paper's result and write down the engineering challenges
Study data loading and distributed training concepts

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 G-Research’s site before applying: requirements, location and pay can change after we check them.

View the posting on G-Research’s site ↗

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