Senior ML Engineer - Underwriting & Decisioning

FloatMe; San Antonio (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

FloatMe in the United States is seeking a Senior Machine Learning Engineer to own and evolve underwriting and decisioning models that determine approvals, amounts, and terms for customers across diverse profiles.

You will work across the full modeling lifecycle—from problem formulation and feature development to deployment, monitoring, and iteration in production—collaborating with Product, Engineering, Legal, Compliance, and Operations to align with business goals and regulatory expectations.

Qualifications

• Master's degree in a quantitative field (e.g., Math, Stats, CS) or PhD preferred.
• 5+ years applying AI/ML in decisioning contexts (credit, risk, etc.).
• Experience with probabilistic models, calibration, score transformations, and interpretation of outputs.
• Strong experimentation skills: holdouts, lift, model evaluation beyond aggregates.
• Experience with model monitoring, degradation detection, and retraining in production.

Responsibilities

• Own and evolve underwriting and decisioning models across the full modeling lifecycle.
• Build, evaluate, and maintain underwriting models and decision frameworks.

Skills

Python

Probabilistic modeling

Experimentation

Model deployment

Stakeholder communication

Education

Master's degree in a quantitative field

PhD welcomed

Tools

NumPy

Pandas

scikit-learn

PyTorch

XGBoost

LightGBM

SQL

Snowflake

GitHub

AWS

Looker

PowerBI

Tableau

Job description

FloatMe in the United States is seeking a Senior Machine Learning Engineer to own and evolve underwriting and decisioning models that determine approvals, amounts, and terms for customers across diverse profiles.

You will work across the full modeling lifecycle—from problem formulation and feature development to deployment, monitoring, and iteration in production—collaborating with Product, Engineering, Legal, Compliance, and Operations to align with business goals and regulatory expectations.