Quant jobs / DRW

Machine Learning Engineer – Algorithmic Trading

An engineering role inside an algorithmic trading research group. You build the infrastructure that lets researchers run and speed up machine learning on very large data.

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.

Build infrastructure to run ML on large datasets and a compute grid
Optimise ML algorithms to meet latency limits
Write software to collect and clean hundreds of terabytes of data
Build visualisation tools for feature exploration and model checks
Plug ML models into strategy simulations

What they ask for

Required

5+ years of modern C++ and Python
Object-oriented design, data structures and algorithms
Numerical computing and machine learning
Advising researchers on engineering practice
Writing algorithmic code quickly

Education: BSc or MSc in computer science, computer engineering or related
Experience: 5+ years of software development
Languages and tools: C++
Python

How to prepare

Write a parallelised feature-computation job in C++ and Python
Learn model inference optimisation and profiling
Practise cleaning large time series datasets
Build a feature-exploration dashboard

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

View the posting on DRW’s site ↗

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