Machine Learning Engineer

Summary:

Fantastic opportunity to work at a tech-centric prop trading fund which trades a wide range of financial products, with offices across the globe. Looking for a pragmatic ML Engineer with strong mathematical foundations to join their growing ML team and help drive the direction of the ML platform.

In this role, you’ll draw on your in-depth knowledge of the ML ecosystem and understanding of varying approaches – whether it’s neural networks, random forests, gradient-boosted trees, or sophisticated ensemble methods – to aid decision-making, choosing the right tool for the problem. Your work will also focus on enhancing research workflows to tighten feedback cycles. Successful ML engineers will be able to understand the mechanics behind various modeling techniques, while also being able to break down the mathematics behind them.

The ideal candidate will be passionate about the craft of software engineering, who enjoys designing APIs systems that colleagues love to use. If you also have a great appetite for learning new things, this role is for you!

Requirements:

You have previously built and maintained training and inference infrastructure
A robust understanding of what it takes to move from concept to production
Strong experience in model training & mathematical concepts, e.g. linear algebra, greek alphabet, choice of loss functions, regularization techniques, model architecture, optimizer, learning rate schedules, etc.
Thorough understanding of Python tools and libraries, keen to offer advice on best practices
Experience using Jax, Tensorflow or similar ML frameworks a huge plus

Benefits:

Generous benefits package, including physical & mental health benefits, excellent holiday entitlement, significant parental leave, retirement benefits, private on-site gym
Focus on learning & development with tuition reimbursement
Recreation spaces with breakfast, lunch, snacks and treats

Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.