Senior Machine Learning Engineer

Our client, financial services technology is seeking a Senior Machine Learning Engineer to join their team. As a Senior Machine Learning Engineer, you will be part of the 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.

Job Title: Senior Machine Learning Engineer

Location: Plano, TX

Pay Range: $70-$73/hr

• 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.

• 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, Num Py, 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.

• 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.

Manpower Group® (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast‑changing world of work by sourcing, assessing, developing, and managing the talent that enables them to win. We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills.

Our expert family of brands
- Manpower, Experis, Talent Solutions, and Jefferson Wells - creates substantial value for candidates and clients across more than 75 countries and territories and has done so for over 70 years. We are recognized consistently for our diversity - as a best place to work for Women, Inclusion, Equality and Disability and in 2023 Manpower Group was named one of the World's Most Ethical Companies for the 14th year - all confirming our position as the brand of choice for in‑demand talent.

Manpower Group is committed to providing equal employment opportunities in a professional, high quality work environment. It is the policy of Manpower Group and all of its subsidiaries to recruit, train, promote, transfer, pay and take all employment actions without regard to an employee's race, color, national origin, ancestry, sex, sexual orientation, gender identity, genetic information, religion, age, disability, protected veteran status, or any other basis protected by applicable law.