5-7 years of experience in machine learning or AI roles
Proven track record of developing and deploying ML models in production
Strong understanding of model evaluation and failure modes
Experience with large, complex datasets
Ability to independently tackle open-ended research problems
BS, MS, or PhD in Computer Science or related field, or equivalent experience
Responsibilities
Identify predictive signals from diverse financial datasets
Design experiments to differentiate genuine improvements from noise
Develop robust ML research systems for rapid experimentation
Transform research findings into production-ready models
Utilize real-world outcomes to enhance model performance
Benefits
Comprehensive medical, dental, and vision coverage
Catered lunches provided
Commuter benefits available
Relocation allowance offered
Continuing work visa sponsorship for full-time employees
Full Job Description
About the Role
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.
Challenges You'll Work On
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.
About You
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.
Nice to Have
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).
Location
Hybrid, 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.
Benefits
We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches, commuter benefits, and more.
Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.
