Machine Learning Engineer- Decision Logic/Underwriting

Qualifications

• 3+ years of experience in ML, data science, or applied AI — ideally within finance, credit risk, or lending environments
• Strong skills in Python, SQL, and ML frameworks like Scikit-Learn, XGBoost, PyTorch, or TensorFlow
• Background working with financial or transactional datasets and credit-scoring or underwriting models
• Familiarity with API integrations and cloud platforms (AWS/GCP)
• Curiosity and the ability to translate complex data into actionable credit insights
• Experience in private credit, alternative lending, or fintech
• Knowledge of model governance, explainable AI (SHAP, LIME), or regulatory compliance frameworks
• A mindset that blends data-driven problem solving with an understanding of financial risk dynamics

Responsibilities

• Build and train machine learning models that power funding and underwriting decisions
• Work with structured and unstructured financial data, including OCR-extracted bank statements and third-party APIs (Plaid, Ocrolus, Datamerch, Unicourts, etc.)
• Develop and maintain feature pipelines and data workflows that feed credit-decision systems
• Deploy and monitor production models to ensure accuracy, scalability, and compliance
• Collaborate cross-functionally with our credit, risk, and data teams to align model outputs with real-world lending performance
• Analyze deal and repayment data to continuously improve model performance and predict risk-adjusted returns

Full Description

Are you passionate about using data to transform how funding and credit decisions are made?

Join Pinnacle Private Credit, where we're combining financial expertise with cutting-edge machine learning to reshape the world of private credit and alternative lending.

We're looking for a Machine Learning Engineer to build the brains behind our decisioning engine — the models that determine how merchants are evaluated, funded, and monitored.

This is a chance to work at the intersection of finance, data science, and technology, building models that drive real impact.

What You'll Do

• Build and train machine learning models that power funding and underwriting decisions.

• Work with structured and unstructured financial data, including OCR-extracted bank statements and third-party APIs (Plaid, Ocrolus, Datamerch, Unicourts, etc.).

• Develop and maintain feature pipelines and data workflows that feed credit-decision systems.

• Deploy and monitor production models to ensure accuracy, scalability, and compliance.

• Collaborate cross-functionally with our credit, risk, and data teams to align model outputs with real-world lending performance.

• Analyze deal and repayment data to continuously improve model performance and predict risk-adjusted returns.

What You'll Bring

• 3+ years of experience in ML, data science, or applied AI — ideally within finance, credit risk, or lending environments.

• Strong skills in Python, SQL, and ML frameworks like Scikit-Learn, XGBoost, PyTorch, or TensorFlow.

• Background working with financial or transactional datasets and credit-scoring or underwriting models.

• Familiarity with API integrations and cloud platforms (AWS/GCP).

• Curiosity and the ability to translate complex data into actionable credit insights.

Bonus Points If You Have

• Experience in private credit, alternative lending, or fintech.

• Knowledge of model governance, explainable AI (SHAP, LIME), or regulatory compliance frameworks.

• A mindset that blends data-driven problem solving with an understanding of financial risk dynamics.