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

Apply Now

Machine Learning Quant Engineer - Investment banking

London
2 months ago
Applications closed

Related Jobs

View all jobs

Graduate Analyst / Consultant

Graduate Analyst/Consultant

Machine Learning Engineer (Databricks)

Machine Learning Engineer - London

Machine Learning Engineer

Data Engineer

Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London.

Inside IR35, 4 days a week on site

The role:

To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact, front-office role offering direct collaboration with traders, quant researchers, and technologists at the forefront of financial innovation.

Your Role

Design, build, and deploy state-of-the-art ML models for alpha generation, portfolio construction, pricing, and risk management
Lead ML research initiatives and contribute to long-term modeling strategy across asset classes
Architect robust data pipelines and scalable model infrastructure for production deployment
Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes
Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets
Collaborate closely with cross-functional teams, including traders, data engineers, and software developersWhat We're Looking For

Required:

7+ years of experience in a quant/ML engineering or research role within a financial institution, hedge fund, or tech firm
Advanced degree (PhD or Master's) in Computer Science, Mathematics, Physics, Engineering, or related discipline
Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL
Expert-level programming skills in Python and strong understanding of software engineering best practices
Experience deploying ML models to production in real-time or high-frequency environments
Deep understanding of financial markets and quantitative modelingPreferred:

Experience in front-office roles or collaboration with trading desks
Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives)
Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines
Exposure to LLMs, graph learning, or other advanced AI methods
Strong publication record or open-source contributions in ML or quantitative finance

Please apply within for further details or call on (phone number removed)

Alex Reeder

Harvey Nash Finance & Banking

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.

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

As we move into 2026, the UK robotics jobs market is in a strange but interesting place. On one hand, UK manufacturers, logistics firms and warehouses must automate to stay competitive, tackle labour shortages and meet productivity and net-zero targets. On the other hand, the UK still lags badly behind peers in robot adoption, with relatively low robot density in factories compared with other advanced economies – which is both a challenge and a massive opportunity. The National Robotarium +1 Add in AI, computer vision and edge computing, and you get a robotics landscape that is: More selective in hiring. More focused on real operational outcomes. More integrated with software, data and safety standards. Whether you are a robotics job seeker planning your next move, or a recruiter building automation and robotics teams, this guide explores the key robotics hiring trends for 2026.

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

Summary: UK robotics hiring has shifted from toolbox checklists to capability‑driven evaluation that emphasises deployed systems, safety, reliability and total cost of ownership. Employers want proof you can ship and sustain robots in production—industrial arms & cobots, AMRs/AGVs, field robots, surgical/med‑tech, warehouse automation, inspection & maintenance. This guide explains what’s changed, what to expect in interviews and how to prepare—especially for robotics software engineers (ROS/ROS 2), perception/vision engineers, controls & motion planners, mechatronics & embedded, safety & compliance, test/V&V, DevOps/SRE for fleets, and robotics product managers. Who this is for: Robotics software/perception/controls engineers, mechatronics & embedded, simulation & test, DevOps/SRE for robotics fleets, HRI/UX, safety/compliance, field/commissioning engineers, and product/technical programme managers in the UK.

Why Robotics Careers in the UK Are Becoming More Multidisciplinary

Robotics used to be the domain of mechanical, electrical and software engineers. In the UK today, robotics is more than motors and control loops — it’s about perception, interaction, trust, regulation and integration into human environments. That evolution means robotics careers are becoming more multidisciplinary. Modern robots interact with people, collect data, operate under constraints, and often assist in safety-critical environments (healthcare, manufacturing, transport). So engineers now collaborate closely with legal, ethical, psychological, linguistic and design experts. In this article, we explore why UK robotics careers are evolving into multidisciplinary roles, how law, ethics, psychology, linguistics & design intersect with robotics, and how job-seekers and employers can adapt to this shift.