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Poesis

Head of AI

Zürich, Switzerland +2

Location
Zurich, ZH, Switzerland · London, England, United Kingdom · Menlo Park, United States
Work
Hybrid
Employment
Full-time
Level
Director
Function
Data & AI
Pay
Not stated
Posted
8 days ago

About the role

About Poesis

Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.

About the Role

Financial markets offer something rare in AI research: a continuous, objective feedback loop where you can test new ideas, measure whether they actually work, and use real-world outcomes to inform what you build next. It’s an opportunity to do frontier research with a direct line between the ideas you explore and their real-world performance. As Head of AI, you’ll lead Poesis’s AI strategy and research, setting the technical direction for how we apply frontier AI to investing. You’ll explore new AI approaches, tackle difficult research problems and help define how we use AI to better understand and predict financial markets. This is a hands-on leadership role where you’ll set the research agenda while continuing to work directly on technical challenges.

Challenges You’ll Work On

  • Set Poesis’s AI research direction, identify the hardest problems worth solving and guide the team's technical work.
  • Push the capabilities of foundation models, agentic systems and world models through new architectures and research approaches.
  • Explore pre-training, mid-training and post-training methods to improve how models learn, reason and adapt.
  • Advance tabular ML research, including emerging methods such as prior-data fitted networks (PFNs).
  • Tackle the challenges of learning from small, high-dimensional datasets where traditional ML methods struggle.
  • Turn promising research into models and systems that can solve difficult real-world problems.

About You

  • You’ve done exceptional AI research at a frontier AI lab, leading research initiatives and helping set technical direction.
  • You have deep expertise in modern AI architectures, model training and machine learning.
  • You have a strong research track record, including relevant publications.
  • You have strong mathematical and statistical foundations and know how to tackle difficult problems with limited, complex data.
  • You’re a hands-on technical leader who can guide other researchers while developing, testing and implementing your own ideas.

Nice to Have

  • Experience with frontier tabular ML methods.
  • Experience applying ML to financial markets or complex, high-dimensional datasets.

Location

Hybrid, 3 days per week on-site at our office in Menlo Park, CA, London, or Zurich. Relocation allowance available.

Compensation

Competitive cash compensation commensurate with experience, plus equity and carry (share of fund profits).

Benefits

We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches, commuter benefits, and more.

For U.S. candidates, current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.

Working at Poesis

As an early team member, you’ll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You’ll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.

Source

Posted by Poesis on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 00:05 UTC; the original is the reference.

View the original ad ↗

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