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

Apply Now

Machine Learning Researcher | London, UK

AAA Global
City of London
1 week ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Location: London, UK

Domain Focus: Global Macro, Multi-Asset Class Alpha Signal Generation, Portfolio Optimisation

Experience: 4+ years experience in a top-tier quantitative firm.

International Talent: Yes, international applicants are encouraged.


These roles are for a professional with a global perspective, ready to apply their sophisticated expertise in machine learning to London’s prestigious financial markets.


Are you interested in joining environments where your research will directly influence strategies with a substantial AUM? Individuals who are seeking to combine intellectual rigor with real-world impact, shaping the future of quantitative and discretionary trading should take this opportunity seriously.


🔷 The Profile – Your Expertise

We’re looking for professionals with a global perspective, skilled in applying advanced machine learning techniques to financial data. They have a demonstrable history of developing and deploying sophisticated models in institutional settings, with deep expertise in risk management and the ability to integrate cutting-edge research into scalable, robust trading platforms that meet the highest standards of institutional finance.


Career Path:

  • Career trajectories focused on applying ML to solve complex problems in global, institutional trading environments.
  • Histories of delivering high-impact projects that directly influence multi-million-dollar portfolios.


Projects And Performance:

  • Experience developing models for global macro, equity, or FX strategies within highly regulated environments.
  • Proven records of backtesting and validating models against diverse historical and real-time datasets.


Professional Skills:

  • Exceptional communication abilities to explain technical complexities and risk profiles to portfolio managers and senior leadership.
  • Expertise in project management within formal, institutional frameworks.


Technical Prowess:

  • Fluency in Python with strong command of machine learning libraries.
  • Familiarity with production-level code, version control (e.g., Git), and high-performance computing environments.
  • Contributions to the development of systematic trading strategies that have been successfully deployed.
  • Histories of rigorous model validation and performance analysis, with emphasis on avoiding overfitting and managing risk.


Qualifications, Licenses And Academic Achievements:

  • Ph.D. in a quantitative field highly preferred.
  • Published research in top-tier academic journals or conferences is a significant plus.


🔷 Who You Are And What We Need

  • Collaborative professionals who thrive in sophisticated, multi-disciplinary team settings.
  • Fit cultures that value intellectual honesty, institutional stability, and a global perspective.
  • Highly motivated individuals with strong accountability and commitment to institutional-grade research and implementation.
  • Adaptable mindsets, capable of navigating dynamic regulatory and market environments in global financial hubs.


If you're ready to lead with conviction and build something enduring, we want to hear from you.


Apply Above Or Connect Directly:

| www.aaaglobal.co.uk


Discreet conversations are always welcome (if concerned contact us directly)

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.

Jobs

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.

Jobs

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.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.