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Hunter Bond

Machine Learning Researcher – Quantitative Trading : PhD ML : London

London
Posted 1 day ago
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Machine Learning Researcher – Quantitative Trading : PhD ML : London

We’re partnering with a globally respected proprietary trading firm to hire a Machine Learning Researcher for a high-impact role embedded directly with a trading desk. This is an opportunity to work at the intersection of machine learning, quantitative research, and production-grade engineering within a firm known for technical excellence and intellectual rigor.

The Opportunity

This role sits within a highly collaborative ML research group working closely with a live trading desk. You’ll be responsible for building and deploying machine learning systems that directly influence trading decisions. The work spans the entire lifecycle — from early research and experimentation through to low-latency, production-ready deployment.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

You’ll join an environment that values autonomy, thoughtful debate, and engineering quality, surrounded by experienced researchers and engineers working on complex, real-world problems.

What You’ll Be Doing

  • Designing and building scalable systems to train and serve machine learning models
  • Owning models end-to-end: research, implementation, deployment, and performance monitoring
  • Improving training and inference efficiency, including hardware-level optimization
  • Adapting models for different compute environments and architectures
  • Leading technical initiatives and influencing system design decisions
  • Contributing to discussions around code quality, testing strategy, and software architecture
  • Collaborating closely with traders, researchers, and engineers across the business

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What We’re Looking For

  • Advanced degree (ideally PhD) in a quantitative or technical discipline such as Machine Learning, Computer Science, Mathematics, Physics
  • 1-3+ years of hands-on experience building machine learning systems in production environments
  • Strong foundations in probability, statistics, and ML theory
  • Proven ability to write high-quality, maintainable, performance-oriented code
  • Experience with MLOps, including model deployment, monitoring, and iteration
  • Publications in NeurIPS, ICLR, ICML etc.
  • GPU programming experience (CUDA, OpenCL)

London based, apply now for more details. Hybrid work culture, top pay and bonuses.

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Skills

Machine Learning
Quantitative Research
Production Engineering
MLOps
Probability
Statistics
GPU Programming
CUDA
OpenCL
Model Deployment
Performance Monitoring
Software Architecture
Code Quality
Testing Strategy
Collaboration
Technical Initiatives

Location

London, England, United Kingdom

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