Senior AI Engineer | Reinforcement Learning x Market Microstructure - London

My client is a confidential, high-conviction quant pod looking for a Senior AI Engineer to help build its strategy intelligence layer from the ground up.

The core question they are trying to answer: Can you observe a world-class discretionary trader and teach a machine to replicate that edge?

The work spans:

• Inverse reinforcement learning over real trade blotters

• Imitation learning distilled into regime-aware execution agents

• Transformer models operating on live L2 order book data

• Multi-agent RL systems optimising order-splitting under non-stationary market conditions

• LLM-driven pipelines converting proprietary research into structured signal priors in real time

Your models run directly in production. You sit with PMs and researchers. No unnecessary layers or bureaucracy.

The broader platform is multi-strategy, with exceptional risk-adjusted performance and ultra-low-latency infrastructure. The team itself includes engineers and researchers from leading HFT and systematic trading firms.

This is a role for engineers who find market microstructure as compelling as model architecture, and who read Hasbrouck for fun.

If your background spans deep learning, reinforcement learning, or applied AI within trading environments, I would genuinely love to speak with you.

If terms like Kyle’s Lambda, Amihud illiquidity, state-space models, or temporal convolutional networks are already part of your vocabulary, even better.

The role is confidential and off-market.

DM me directly or drop me an email for further details. Full information available under NDA.

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