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

Apply Now

React Developer - Quantitative & Systematic Trading Technology - Up to £140k + Excellent Bonus & Benefits

Hunter Bond
London
1 year ago
Applications closed

Related Jobs

View all jobs

Scientific Data Scientist

Data Engineer | SC Cleared

Full Stack Data Engineer

Senior Data Engineer

Staff AI Agent Engineer (Machine Learning)

Senior Data Engineer

Hunter Bond have partnered with a top global Quantitative & Systematic hedge fund that are currently looking to add talented Frontend Developers to a critical team that is responsible for building and maintaining machine learning frameworks, data science tools, microservices and various other data driven applications to support it's various trading strategies.


This is an excellent opportunity to work with the latest technologies, whilst working closely with front office investment teams to build complex solutions to deliver on high impact business goals and priorities.


Key Requirements:

  • 3+ Years Frontend Development Experience
  • React, Redux & Typescript & GraphQL
  • Knowledge of any app/tool to display large volumes of data
  • Knowledge of Rust or Python is beneficial but not essential
  • Comp Sci / STEM Degree from a reputable uni


This position is paying up to £140k + Bonus & Benefits.


Please apply with an up to date CV for more information or recommend someone in your network and get rewarded if we are successful in securing them a new role.

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.