2027 Shanghai Machine Learning Engineer Summer Internship

As a Machine Learning Engineer Intern at Optiver, youll work alongside experienced engineers on high-performing systems that respond to live financial markets in real time.

Youll contribute to the compute platforms and libraries that support large-scale machine learning model training and simulation workloads, gaining hands-on experience applying modern ML techniques to real quantitative trading problems. Within weeks, you could be building tools or models that run in production and directly support our trading strategies.

By the end of the 8-week internship, youll have a clear and practical understanding of how technology and ML techniques are used in the quantitative trading industry. Plus, if youve excelled over the summer, youll receive an offer to return as a Machine Learning Engineer. 

What youll do:

Led by our in-house education team that consists of ex-traders and engineers, youll delve into advanced engineering concepts and lead innovative projects, during our world-class training program.

In just a few weeks, you'll have the opportunity to:

• Gain first-hand experience applying the latest ML methodologies to quantitative trading problems.

• Help build the compute platform and libraries for large scale ML model training and simulation workloads.

• Manage a project end-to-end, learn how to work with a complex code base and make impactful contributions to production systems.

• Work on real trading and IT problems, both technically and functionally, to improve our trading success.

Throughout the program, you'll be paired with an experienced mentor, who will show you the ins-and-outs of our trading systems, and provide you with guidance and feedback.

Additionally, internal resources will be available for your continuous learning and development.

What youll get:

Youll join a culture of collaboration and excellence, where youll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, youll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the most complex problems in the financial markets.

In addition, youll receive:

• A highly competitive remuneration package.

• Optiver-covered flights and accommodation for the duration of the internship.

• The opportunity to work alongside diverse and intelligent peers in a rewarding environment.

• Training, mentorship and personal development opportunities.

• Gym membership, plus weekly in-house chair massages.

• Daily breakfast, lunch and in-house barista.

• Regular social events.

Who you are:

• Students graduating in 2028 or later.

• Foundations in Machine Learning, including optimisation and deep learning concepts.

• Hands-on experience with deep learning frameworks such as PyTorch, JAX, or similar.

• Interested in building scalable and reproducible machine learning pipelines, including data preprocessing, training, evaluation, and experiment tracking.

• Natural problem solvers who love tackling a complex technical challenge.

• Team players who thrive in collaborative environments and are eager to learn, iterate, and improve.

• Interested in the trading / quantitative finance industry (prior finance knowledge is not required).

  Optional:

• Ability to identify and reason compute and performance bottlenecks, using profiling, benchmarking, and systematic analysis to improve training efficiency.

• Experience with distributed training or GPU acceleration is a plus.

• Familiarity with experiment management tools (e.g. MLflow, Weights & Biases) or workflow orchestration is a plus.

How to apply:

Dont miss your chance to accelerate your career and thrive on one of the most dynamic trading floors in mainland China. Apply now via the form below.

In your application, please submit the following materials in English:

• Resume

• Cover letter (optional)

Questions? Please email

We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can re-apply when the next recruitment season begins in 2027.

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