Lead Machine Learning Engineer

Overview
Lead Machine Learning Engineer role at Mastercard.
We are seeking a highly skilled and forward-thinking machine learning engineer to lead the development and deployment of scalable ML systems that drive innovation and deliver measurable impact across the business.
The ideal candidate combines deep technical expertise with strong engineering discipline and a passion for solving real-world problems, including building robust ML pipelines, optimizing model performance, and collaborating with cross-functional teams to integrate intelligent solutions into production environments.
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 initiatives and projects to build and deploy ML systems that solve critical business questions and automate decision-making processes.
Translate client/stakeholder needs into machine learning solutions in collaboration with internal and external partners and present findings and outcomes to clients/stakeholders.
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.
Guide others to develop sophisticated ML models and engineering solutions (e.g., recommendation systems, anomaly detection engines, predictive maintenance tools) utilizing supervised, unsupervised, and reinforcement learning techniques.
Delegate and review work for junior-level colleagues to ensure downstream applications and tools are not compromised or delayed.
Serve as a technical coach for junior-level colleagues and develop technical talent via ongoing technical training, peer review, and mentorship.
All About You
Proven experience designing, building, and deploying machine learning systems in production.
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.
Excellent communication and stakeholder management skills.
Demonstrated ability to mentor and grow technical teams.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks come with inherent risk to the organization and every person must be responsible for information security.
Abide by Mastercard's security policies and practices; ensure the confidentiality and integrity of information; report any suspected information security violation or breach; complete periodic mandatory security trainings.
Seniority, Employment, and Function
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Financial Services, IT Services and IT Consulting, and Technology, Information and Internet
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