R-252168 Director, Software Engineering

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.

Director, Software Engineering

Director AI/ML & Data Science Engineer, Infrastructure and Automation Services

Background

Infrastructure and Automation Services (IAS) is a team of software engineers responsible for designing and implementing automation services across Mastercard’s distributed infrastructure. The IAS team is looking for a Senior Software Development Engineer to design, develop, and implement Java-based solutions for infrastructure automation that improve developer experience, operational efficiency, and system reliability.

The Role

We are seeking a highly experienced and visionary Lead Data Science and AI/ML Engineer to drive the development and deployment of cutting-edge machine learning models and data-driven solutions across our organization. This role blends hands-on engineering expertise with strategic leadership, focusing on building scalable systems, guiding model lifecycle management, and unlocking business value through AI innovation.

You will collaborate closely with product, engineering, data, and business stakeholders to design, deliver, and continuously improve AI/ML applications that power our core products and services.

Key Roles and Responsibilities

Leadership & Strategy

Lead cross-functional AI/ML initiatives from concept to production, including experimentation, deployment, and monitoring.

Define and evolve the AI/ML strategy in alignment with business goals and ethical AI practices.

Mentor and grow a team of data scientists, machine learning engineers, and analysts.

Serve as a technical advisor to executives on AI strategy, model risk, and innovation opportunities.

Model Development & Engineering

Design, build, and optimize ML models using Python, TensorFlow, PyTorch, Scikit-learn, or similar frameworks.

Architect scalable data pipelines and model serving infrastructures on cloud platforms (AWS, GCP, Azure).

Implement ML Ops best practices: CI/CD for models, version control, reproducibility, monitoring, and retraining.

Conduct model performance analysis, A/B testing, and error diagnostics to ensure business impact and fairness.

Data Science & Insights

Develop predictive, descriptive, and prescriptive models for real-time and batch use cases.

Collaborate on experiment design, causal inference, and hypothesis testing.

Drive data storytelling and actionable insight delivery through dashboards and stakeholder engagement.

Governance & Responsible AI

Ensure AI systems are explainable, transparent, and compliant with regulatory or internal policies.

Champion fairness, bias mitigation, and human-centered AI principles.

Education & Required Qualification

6+ years of experience in data science, machine learning, or applied AI roles.

Advanced proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and at least one deep learning framework.

Experience leading teams and projects involving production-grade ML systems.

Strong understanding of statistics, experimental design, and optimization techniques.

Familiarity with cloud-based ML tools (e.g., SageMaker, Vertex AI, Azure ML) and big data platforms (e.g., Spark, Databricks).

Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field. PhD a plus.

Knowledge / Experience

Experience in GenAI / LLM fine-tuning, prompt engineering, or RAG pipelines.

Knowledge of data privacy frameworks (GDPR, HIPAA, etc.) and model governance.

Familiarity with containerization (Docker, Kubernetes) and model monitoring tools.

Publications, patents, or open-source contributions in ML/AI.

Why Join Us

Lead high-impact AI initiatives that shape the future of our business.

Work in a supportive, innovation-driven culture with cutting-edge infrastructure.

Influence product and platform strategy while mentoring the next generation of AI talent.

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.