Poesis Inc. · 2 months ago
Founding Machine Learning Data Scientist
San Francisco, CA
Full-time
Hybrid
Senior Level
5+ years expPoesis Inc. is an AI-native investment manager pioneering a new foundation model for investing in U.S. equities. The Founding Machine Learning Data Scientist will be responsible for building end-to-end machine learning pipelines and shaping investment decisions through the implementation of production models.
Computer Software
Responsibilities
Architect, build, and maintain the core ML infrastructure for Poesis’ investment platform
Develop reproducible pipelines for data ingestion, feature generation, and model training
Implement backtesting and evaluation frameworks with clear performance metrics
Deliver regular, documented reports on model accuracy, feature importance, and portfolio-level impact
Collaborate closely with the Chief Scientist to refine model hypotheses and production readiness
Maintain code quality: version control, testing, reproducibility, and documentation
Build robust backtesting frameworks and model validation tools with walk-forward evaluation and risk controls
Integrate with professional financial data providers (Bloomberg, FactSet, Refinitiv, CapIQ)
Establish foundational MLOps practices: model versioning, CI/CD, monitoring, and documentation
Define and iterate on “demo-able” workflows that connect model outputs to investment decision-makers
Qualification
Required
5–10+ years of experience as an ML Engineer, Quant Engineer, or similar role
Proven track record deploying production ML systems (ideally in finance or other high-stakes domains)
Deep expertise in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, JAX, XGBoost)
Experience designing large-scale, reliable data or MLOps systems
Strong software engineering fundamentals: testing, versioning, CI/CD, and code review discipline
Experience with financial data APIs and real-time data handling
Comfortable working directly with executives and acting as both IC and product owner
Willingness to work in-person in the Bay Area; relocation support available
Preferred
Prior experience at a hedge fund, quant research lab, or fintech startup
Familiarity with quantitative finance, portfolio optimization, or risk management
Exposure to time-series modeling, forecasting, or reinforcement learning
Understanding of financial market microstructure and execution systems
Experience with LLM/RAG workflows for parsing financial documents (filings, transcripts)
Comfort with multi-language engineering environments (C++, Rust, Go, etc.)
Benefits
High quality dental, vision, and health care
Company
Poesis Inc.
Poesis is the AI-native investment manager pioneering a new foundation model for investing.
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase