Quant jobs / Optiver

Senior Machine Learning Engineer

A senior engineering role running the compute platform and ML libraries for a new AI lab. The lab operates separately from core trading as a long-term AI innovation team.

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.

Run and stabilise CPU and GPU clusters for ML workloads
Add monitoring so the platform is observable and scalable
Profile cluster bottlenecks across infrastructure and software
Support petabyte-scale model training and simulation

What they ask for

Required

Production ML infrastructure at scale
Linux computing environments
Containerisation
Parallel computing and distributed training
Storage for data-intensive clusters

Preferred

Supporting ML researchers in production

Education: No degree level stated.
Experience: Solid experience running large-scale production ML infrastructure

How to prepare

Set up a small GPU cluster job with containers and monitoring
Learn distributed training approaches such as data and model parallelism
Study storage options for very large training datasets
Practise profiling cluster utilisation

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.