I am recruiting on behalf of a confidential hedge fund building out its deep learning and mid-frequency ML research team. This is a hands-on role working directly alongside the team lead, applying deep learning to high- and mid-frequency trading data.

Aboue the role:

• Build and apply deep learning models to high-frequency and mid-frequency trading data.
• Work side-by-side with the team lead — this is a hands-on builder role, not a remote strategy or oversight position.
• Own the full modeling lifecycle, from research and experimentation through to training and deployment on large-scale models.
• Operate in a fast-moving, performance-driven environment where research directly informs trading decisions.
• Collaborate closely with a small core team, with room to shape the research direction as the team grows.


What we're looking for

• Top-tier university background.
• Minimum of a Master's degree with solid hands-on experience.
• A PhD with 1–2+ years of practical research or industry experience is strongly preferred.
• Must know how to train large-scale models — this is essential, not optional.
• Background in a top AI lab (e.g., DeepMind, OpenAI) or a strong practical research track record.
• We're deliberately less interested in candidates from large multi-strategy quant funds, where researchers tend to be siloed — strong practical backgrounds are valued over brand-name fund experience.
• Comfort working directly with a team lead in a fast-moving, performance-driven environment.