Poesis AI
Poesis AI
Poesis AI este un administrator de investiții construit în jurul inteligenței artificiale, care dezvoltă un model investițional de mari dimensiuni, aflat într-un proces continuu de învățare, pentru investitori profesioniști și instituționali. Platforma antrenează agenți în medii de piață bogate în date, pentru a genera semnale de tranzacționare, a testa strategii, a aloca capital și a gestiona riscul pe piețele financiare în timp real. Activitatea sa reunește inteligența artificială, învățarea automată și administrarea portofoliilor, iar echipa are experiență în finanțe și învățare automată.

Lead Machine Learning Engineer, Financial AI

Develop predictive signals, production machine learning models, and evaluation systems for Poesis AI’s autonomous investment platform. Apply AI to financial data and use investment outcomes to improve models and agents.

Descriere

  • Identify predictive signals across financial, fundamental, and alternative datasets
  • Design experiments to distinguish meaningful model improvements from noise
  • Create reproducible machine learning research systems for rapid experimentation
  • Translate promising research into durable production models and signals
  • Use real-world outcomes to identify opportunities to improve models and agents
  • Develop models, signals, and evaluation tools for alpha discovery, decisions, and risk management
  • Analyze complex financial data and inform investment decisions
  • Help shape the product and company operations as an early team member
  • Develop from first principles without legacy systems or established processes

Cerințe

  • Background at a frontier AI lab, agent-focused startup, high-growth technology company, leading investment manager, or comparable organization
  • Experience developing, evaluating, and deploying machine learning models in production
  • Understanding of model failure modes and evaluation design, including how to distinguish promising results from noise
  • Strong quantitative judgment
  • Experience working with large, complex datasets
  • Ability to own open-ended research problems and use evidence to determine what to pursue
  • Bachelor’s, master’s, or doctoral degree in computer science or a related field, or equivalent practical experience
  • Experience building machine learning or AI systems with financial, fundamental, alternative, or time-series data
  • Familiarity with quantitative investing, portfolio construction, or risk management
  • Experience applying modern AI systems to financial documents
  • Current legal authorization to work in the United States

Beneficii

  • Equity
  • A share of fund profits through carry
  • Comprehensive medical coverage
  • Dental coverage
  • Vision coverage
  • Catered lunches
  • Commuter benefits
  • Relocation allowance
  • Continuing work visa sponsorship for full-time employees

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