Member of Technical Staff | Machine Learning

Poesis•Menlo Park, CA

4d•$200,000 - $280,000•Hybrid

About The Position

At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We’re looking for a Member of Technical Staff (Machine Learning) to build the models, signals, and evaluation tools that make this possible. This is an opportunity to test new ideas against complex, real-world financial data and see the impact of your work on actual investment decisions.

Requirements

You’ve worked at a frontier AI lab, agentic startup, high-growth technology company, leading investment manager, or similar organization.
You’ve developed, evaluated, and deployed ML models in production.
You understand how models fail, how evaluation design shapes outcomes and how to distinguish promising results from noise.
You have strong quantitative judgment and experience working with large, complex datasets.
You can take ownership of open-ended research problems and use evidence to decide what to pursue next.
BS, MS, or PhD in Computer Science or a related field, or equivalent practical experience.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.

Nice To Haves

Experience developing ML or AI systems using financial, fundamental, alternative, or time-series data.
Familiarity with quantitative investing, portfolio construction, or risk management.
Experience applying modern AI systems to financial documents (filings, transcripts, etc).

Responsibilities

Find predictive signals in large financial, fundamental and alternative datasets.
Design experiments and evaluations that separate real improvements from noise.
Build rigorous, reproducible ML research systems for fast experimentation.
Turn promising research into production models and signals that hold up over time.
Use real-world outcomes to understand where models and agents can improve.