Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer- World-Leading Prop Trading Fund

Oxford Knight
London
4 days ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

About the Position

My client is a tech-centric prop trading fund, trading a wide range of financial products across the globe. Now looking for an engineer with robust experience in machine learning and strong mathematical foundations to join the growing ML team and to help drive the direction of the ML platform.

Machine learning is a critical pillar of the fund's global business. The ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing new ideas to be incorporated with relatively little friction. The ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use.

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 so that the right tool is applied for the problem at hand. 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.

If you've never thought about a career in finance, you're in good company. Many of the employees were in the same position before working at this firm. While there isn't a fixed list of qualifications they're looking for, if you have a curious mind and a passion for solving interesting problems, you'll almost certainly fit right in.

Requirements:

  • Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
  • A strong mathematical background; good candidates will be excited about things like optimization theory, regularization techniques, linear algebra, and the like
  • A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
  • A proven ability to create and maintain an organized research codebase that produces robust, reproducible results while maintaining ease of use
  • Expertise wrangling an ML framework - they're fans of PyTorch, but they'd also love to learn what you know about Jax, TensorFlow, or others
  • An inventive approach and the willingness to ask hard questions about whether the right approaches are being taken and the right tools being used
  • Fluency in English



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.

Contact
If this sounds like you, or you'd like more information, please get in touch:

George Hutchinson-Binks

(+44)
linkedin.com/in/george-hutchinson-binks-a62a69252

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.