Senior Machine Learning Engineer

About the role

Our client, a financial services technology company located in Plano, TX, is seeking a Senior Machine Learning Engineer to join their Data Science & Machine Learning organization supporting model development and production integration. The ideal candidate will have hands‑on Python model development experience, strong supervised classification expertise, and the ability to independently deliver end‑to‑end machine learning solutions from exploration through deployment.

Responsibilities

• Design, build, train, validate, and tune supervised machine learning classification models using structured, behavioral, and transactional data.
• Perform hands‑on data exploration, cleansing, transformation, and feature engineering to create reliable inputs for model development.
• Develop repeatable Python‑based workflows, scripts, and pipelines for dataset preparation, model training, evaluation, and scoring.
• Evaluate model performance using classification metrics (precision, recall, F1 score, ROC‑AUC, confusion matrices) and iterate based on false positive/false negative analysis.
• Package and deploy machine learning models into scalable production or near‑production environments in partnership with application and platform engineering teams.

Requirements

• Master’s or PhD in a quantitative or technical field such as computer science, statistics, mathematics, engineering, data science, or a related discipline.
• 5‑10 years of hands‑on data science or machine learning engineering experience delivering models, pipelines, or analytics solutions in highly technical environments.
• Strong Python development experience with libraries such as pandas, NumPy, scikit‑learn, XGBoost, or similar frameworks.
• Deep understanding of supervised machine learning classification, including feature engineering, model training, hyperparameter tuning, validation, threshold selection, and performance evaluation.
• Experience packaging, versioning, testing, and integrating machine learning models or scoring logic into production or near‑production workflows.

Benefits

• Opportunity to independently deliver complex classification models from data exploration through production implementation.
• Work on repeatable Python workflows and pipelines that support reliable model development and scoring.
• Collaborate closely with engineering teams to integrate models into scalable production decisioning workflows.
• Strengthen your technical documentation and communication by clearly capturing assumptions, feature logic, validation results, and operational considerations.
• Contribute to model quality by troubleshooting data quality, pipeline issues, and integration challenges across development, testing, and deployment.

Pay

Pay Range: $70‑$73/hr