Machine Learning Engineer II (Underwriting ML)

For our client, we are seeking a Machine Learning Engineer II (Underwriting ML) to join the team of a leader in the Finance & Insurance space.

This role will focus on developing and improving machine learning models that support underwriting decisions and help strengthen the performance of core credit and risk systems.

You will build scalable data and feature pipelines, prototype new approaches, and work closely with partner teams to move models from experimentation into production.

The position requires strong technical depth in Python, classification modeling, and ML operations, along with the ability to communicate findings clearly across technical and non-technical stakeholders.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $146,000 – $206,000 annually

Responsibilities

• Develop and iterate on underwriting prediction models for tabular and sequential data.
• Build and scale feature pipelines using proprietary and third-party signals.
• Prototype new modeling ideas and run offline experiments to improve model performance.
• Integrate models into decision systems to enhance reliability and operational robustness.
• Monitor model and data health, and define retraining workflows.
• Collaborate with cross-functional teams to define requirements and communicate results clearly.

Qualifications

• 2+ years as a machine learning engineer or a PhD in a relevant field.
• Proficiency in Python and production-quality code development.
• Experience with classification models, preferably using gradient-boosted decision trees such as LightGBM, XGBoost, or CatBoost.
• Familiarity with deep learning frameworks, specifically PyTorch.
• Knowledge of distributed data processing frameworks, with Spark preferred.
• Experience with ML lifecycle tools such as Kubeflow or MLflow.
• Strong communication skills for collaboration with technical and non-technical teams.

Benefits

• 100% subsidized medical coverage for you and your dependents.
• Generous stipends for technology, food, lifestyle needs, and family formation expenses.
• Competitive vacation and holiday schedules for rest and recharge.
• Employee stock purchase plan (ESPP) for discounted shares.

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.