Quant jobs / Optiver

Machine Learning Engineer Summer Internship – 2027

An eight-week internship building compute platforms and libraries for large-scale ML training and simulation. It sits in a market maker's Shanghai technology team and can lead to a full-time offer.

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.

Contribute to the compute platform for model training
Build tools or libraries that run in production
Own a small project end to end in a large codebase
Apply ML methods to a real trading problem

What they ask for

Required

Student graduating 2028 or later
Machine learning foundations including optimisation
Hands-on deep learning frameworks
Interest in scalable ML pipelines
Interest in quantitative trading

Preferred

Profiling and benchmarking bottlenecks
Distributed training or GPU acceleration
MLflow or Weights & Biases

Education: Students graduating in 2028 or later.
Experience: Current students; no finance knowledge required
Languages and tools: Python
PyTorch
JAX

How to prepare

Train a small PyTorch model with experiment tracking
Profile a training loop and speed it up
Build a reproducible pipeline from preprocessing to evaluation
Learn the basics of how ML is used on financial data

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

View the posting on Optiver’s site ↗

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