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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.
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.
संयुक्त राज्य
कैलिफ़ोर्निया$2,00,000 – $2,80,000 / वर्ष
हाइब्रिडपूर्णकालिकलीडआवश्यक भाषा: अंग्रेज़ीमशीन लर्निंग इंजीनियरविवरण
- 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
आवश्यकताएँ
- 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
लाभ
- 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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