Senior Machine Learning Engineer
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Machine Learning Engineer
Overview:
We are seeking a highly skilled and experienced Senior Data Scientist to design, build, and optimize scalable machine learning systems that deliver measurable impact across the business. This role involves developing robust ML pipelines, deploying models to production, and applying advanced techniques to solve complex problems. The ideal candidate is a hands-on technical expert with deep knowledge of machine learning, software engineering, and data infrastructure.
Role:
Responsible for developing machine learning-driven analytical solutions and identifying opportunities to support business and client needs in a scalable and automated manner, facilitating informed recommendations and decisions. Activities include designing and deploying ML models, building end-to-end pipelines, conducting performance analyses, ad hoc reporting, and developing ML-powered data visualizations.
In this position, you will:
Lead complex technical initiatives to build and deploy ML systems that solve critical business questions and automate decision-making processes
Translate business and stakeholder requirements into scalable machine learning solutions and collaborate with engineering and data teams to implement them
Identify rich data sources and oversee the integration, cleaning, and transformation of datasets to ensure consistency and readiness for ML applications
Deliver high-quality ML solutions and tools within agreed-upon timelines and budget parameters and conduct post-implementation reviews
Develop sophisticated ML models and engineering solutions (e.g., recommendation systems, anomaly detection engines, predictive maintenance tools) using supervised, unsupervised, and reinforcement learning techniques
Apply best practices in software engineering, including version control, testing, and continuous integration, to ensure reliability and maintainability of ML systems
Optimize model performance and scalability through hyperparameter tuning, feature selection, and efficient deployment strategies
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All about you:
3 - 5 years proven experience designing, building, and deploying machine learning systems in production environments
Strong proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, PyTorch
Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes)
Solid understanding of ML algorithms, model evaluation, feature engineering, and data preprocessing
Experience with complex neural network architectures and transformer-based models (e.g., BERT, GPT, ViTs) is strongly preferred
Familiarity with MLOps practices including CI/CD, model monitoring, and automated retraining
Strong problem-solving skills and ability to work independently on technically challenging projects
Excellent communication skills and ability to collaborate effectively with cross-functional teams
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard's security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
Perks and Benefits
Health and Wellness
- Health Insurance
- Dental Insurance
- Vision Insurance
- Life Insurance
- Short-Term Disability
- Long-Term Disability
- FSA
- FSA With Employer Contribution
- HSA
- HSA With Employer Contribution
- Fitness Subsidies
- On-Site Gym
- Pet Insurance
- Mental Health Benefits
- Virtual Fitness Classes
- Health Reimbursement Account
Parental Benefits
- Birth Parent or Maternity Leave
- Non-Birth Parent or Paternity Leave
- Fertility Benefits
- Adoption Assistance Program
- Family Support Resources
- On-site/Nearby Childcare
- Adoption Leave
Work Flexibility
- Flexible Work Hours
- Remote Work Opportunities
- Hybrid Work Opportunities
Office Life and Perks
- Commuter Benefits Program
- Casual Dress
- Happy Hours
- Snacks
- Company Outings
- On-Site Cafeteria
- Holiday Events
- Some Meals Provided
Vacation and Time Off
- Paid Vacation
- Paid Holidays
- Personal/Sick Days
- Leave of Absence
- Volunteer Time Off
Financial and Retirement
- 401(K) With Company Matching
- Performance Bonus
- Relocation Assistance
- Financial Counseling
- Stock Purchase Program
- 401(K)
- Company Equity
Professional Development
- Tuition Reimbursement
- Promote From Within
- Mentor Program
- Access to Online Courses
- Lunch and Learns
- Internship Program
- Work Visa Sponsorship
- Leadership Training Program
- Associate or Rotational Training Program
- Shadowing Opportunities
Diversity and Inclusion
- Employee Resource Groups (ERG)