AI Placement - 2027 (Imperial 6 month placement, April - September 2027)

Marshall Wace is recruiting for AI Placement - 2027 (Imperial 6 month placement, April - September 2027) in London. This listing was last seen on the firm's own job board on August 22, 2026.

A London equity manager whose TOPS platform turns broker signals into a systematic process.

What sets Marshall Wace apart: Systematic equity long short rather than high frequency. TOPS platform aggregates external analyst signals, which is unique in the industry. Technology and research hired at similar volume.

Related preparation: Quantitative Researcher (QR) Career Roadmap, Machine Learning Quant Career Roadmap, Quant Strategist (Desk Quant) Career Roadmap, Quant Data Scientist (Alternative Data) Roadmap, Quant Research Ops (MLOps) Roadmap and Financial Data Scientist Career Roadmap.

The role, as Marshall Wace describes it, published on August 10, 2026 and reproduced from their job board:

Join our AI Development teams in London for a 6-month placement where you'll work directly on projects that support Finance, Operations, Risk, Trading and Portfolio Management. This isn't a shadowing programme - you'll be writing production code, shipping features and owning deliverables from day one.

You'll leave with real engineering experience across a range of technologies, a working knowledge of financial markets, and a strong foundation for a career in tech.

About the programme

For Imperial MEng students, over six months, you'll sharpen your skills in AI, software engineering and programming while building a practical understanding of how a systematic hedge fund operates.

You'll join one of our AI-focused teams, which build the services, models and data assets that bring generative AI into Marshall Wace's investment and operations workflows. The goal is straightforward: make it possible for every engineer in the firm to use AI/ML effectively, without needing to be a specialist. Our team holds that specialist knowledge - and during your placement, you'll develop it too.

Day to day, you could be adding features to our AI platform, developing backend services, building LLM pipelines or improving our RAG engine. You'll own specific projects end to end - from design through development, implementation and review - not just contribute to someone else's. For those with a strong interest and aptitude in machine learning, there will also be the opportunity to design and train models for use cases across the firm.

Candidate profile:

Strong coding ability, ideally in Python

Demonstrated interest or coursework in Machine Learning and AI (through personal projects & research)

Curiosity about financial markets (no prior finance experience required)

Please note: