Staff ML Engineer: Finance Market Signals & Risk

Poesis Inc.; Menlo Park (CA); Híbrido; USD 180.000 - 280.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Catered lunches

Commuter benefits

Excellent medical, dental, and vision

Descripción de la vacante

Poesis Inc. seeks a Member of Technical Staff (Machine Learning) to build models, signals, and evaluation tools that drive investment decisions. You will test ideas against real financial data and translate research into production signals.

You will design experiments, deploy ML models at scale, and work on end-to-end systems that improve alpha and risk management with rigorous evaluation and reproducibility.

Formación

• Experience developing, evaluating, and deploying ML models in production.
• Ability to work with large, complex datasets.
• Ownership of open-ended research problems with evidence-based decisions.
• Understanding of model failure modes and evaluation design.
• BS/MS/PhD in CS or related field, or equivalent practical experience.

Responsabilidades

• Find predictive signals in large financial, fundamental, and alternative datasets.
• Design experiments and evaluations that distinguish 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 identify improvements for models and agents.

Conocimientos

ML deployment

Quantitative judgment

Research ownership

Large datasets

Production systems

Educación

BS/MS/PhD in CS or related field

Descripción del empleo

Poesis Inc. seeks a Member of Technical Staff (Machine Learning) to build models, signals, and evaluation tools that drive investment decisions. You will test ideas against real financial data and translate research into production signals.

You will design experiments, deploy ML models at scale, and work on end-to-end systems that improve alpha and risk management with rigorous evaluation and reproducibility.