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Poesis AI
Poesis AI
Dirbtinis intelektasFinansaiFintech
Poesis AI is an AI-native investment manager developing a continuously learning Large Investment Model for professional and institutional investors. The platform trains agents in data-rich market environments to generate trading signals, test strategies, allocate capital, and manage risk in live financial markets. Its work brings together artificial intelligence, machine learning, and portfolio management, with a team drawing on experience in finance and machine learning.
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Darbai įmonėje

Lead Quantitative Finance Engineer

Build AI-driven investment systems at Poesis AI, from financial data pipelines and quantitative models to backtesting and production tools. Partner with research and engineering teams to turn experiments into systems that inform investment decisions.

USJungtinės ValstijosCAKalifornija
180 000 $ – 280 000 $ / metai
HibridinisVisas etatasVadovasPrivaloma Kalba: anglųFinansinis planavimas ir analizė

Aprašymas

  • Turn financial research and model prototypes into reliable production systems
  • Prepare complex financial data for rigorous modeling and investment research
  • Build scalable, reproducible systems for feature generation, backtesting, and model evaluation
  • Stress-test models and signals to identify what holds up and where they fail
  • Solve engineering challenges in moving research from experimentation to production
  • Prepare large financial datasets
  • Design and implement quantitative models and agents
  • Create tools for testing and evaluation
  • Collaborate with the CEO, Chief Scientist, and AI and engineering teams on quantitative systems that support the investment process
  • Bring new ideas from experimentation into production and inform investment decisions

Reikalavimai

  • Build infrastructure, data pipelines, or analytical tools for developing and evaluating financial models or trading strategies
  • Work with complex linguistic and numerical data and produce rigorous, reproducible analysis
  • Bring strong quantitative foundations
  • Reason clearly about statistical and modeling problems
  • Balance rapid iteration with sound engineering quality
  • Explain technical findings and experimental results to leadership and technical and nontechnical audiences
  • Hold a BS, MS, or PhD in Computer Science, Mathematics, Statistics, Physics, Finance, or a related quantitative field
  • Preferred: full-time experience in finance, data science, or machine learning engineering
  • Preferred: experience integrating Bloomberg, CapIQ, FactSet, or Refinitiv data into quantitative research workflows
  • Preferred: familiarity with portfolio optimization, risk modeling, or financial time series
  • Have current legal authorization to work in the United States

Privalumai

  • Equity and carry, a share of fund profits
  • Medical coverage
  • Dental coverage
  • Vision coverage
  • Catered lunches
  • Commuter benefits
  • Relocation allowance
  • Continuing work visa sponsorship for full-time employees

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