Platinum & Partners is retained by a top-tier global hedge fund to identify an experienced Quantitative Developer with a machine learning focus for a collaborative and entrepreneurial systematic macro pod in London. You will develop and deploy machine learning models — classical and deep learning — on high-frequency market data, and build the research and compute infrastructure that underpins them.
Working closely with the Senior Portfolio Manager, you will turn models into live trading signals while extending the pod's wider research infrastructure: distributed computation, large-scale parameter search and a streamlined path from research to production. The firm wants someone who can start as soon as possible.
THE ROLE
- Design, train and productionise large-scale machine learning models across classical and deep learning approaches, applied to high-frequency market data
- Enhance and optimise the pod's end-to-end ML pipeline: large-scale data processing, distributed computation, scalable parameter search and validation
- Improve the speed, scalability and reliability of the pod's signal development environment — ensuring consistent and efficient migration from research to production
- Build data-intensive research tools, model development infrastructure and automated workflows
- Build and deploy agentic AI systems: tool use, orchestration and evaluation
- Partner with broader technology teams to make effective use of shared internal platforms and services
WHAT THEY ARE LOOKING FOR
- Master's or PhD/Post-Doctorate in Computer Science, Mathematics, Statistics, Engineering, Physics or a related quantitative discipline from a leading institution
- 3+ years of professional experience in software engineering, quantitative development or a related computational role
- Experience developing and validating ML models on large, complex datasets — across both classical and deep learning approaches — in industry or academia
- Experience building distributed computing systems for machine learning applications
- Strong Python beyond the standard research stack: parallelism, distributed compute and native acceleration via Python or C++ bindings
- Strong Linux development experience
- C++ familiarity is a strong plus; the software engineering fundamentals to pick it up quickly are equally valued
- Experience building agentic AI systems — tool use, orchestration and evaluation
Particularly valued:
- Experience with backtesting and awareness of common research pitfalls: overfitting, lookahead bias, survivorship bias
- Understanding of systematic trading strategies and quantitative research workflows
- Knowledge of market microstructure
- Experience supporting production research workflows or model deployment in a front-office environment
WHY THIS ROLE
- A top-tier global hedge fund with the data, compute infrastructure and intellectual ambition to work on genuinely hard ML problems in a live trading context
- Collaborative, entrepreneurial systematic macro pod — small, high-calibre team where every person's contribution is visible and valued
- The role spans both model development and infrastructure — you are building the tools and the models, not just one or the other
- Direct collaboration with the Senior Portfolio Manager: your models feed into live trading signals, not internal research reports
- Agentic AI and distributed compute are core to the brief — a forward-thinking team that moves with the technology
- London base — one of the world's deepest pools of systematic macro and ML engineering talent
- Highly competitive total compensation reflecting the seniority and specialisation of this profile