
Global payments and technology company
Lead AI Engineer at Mastercard
About the role
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
Lead AI Engineer:
Overview:
We are seeking a highly skilled and visionary Lead Data Scientist to spearhead the development of advanced AI solutions that drive innovation and deliver measurable impact across the business. This role involves leading complex AI initiatives, architecting scalable machine learning systems, and mentoring a team of engineers and data scientists. The ideal candidate combines deep technical expertise with strategic thinking and strong leadership capabilities.
Role:
Responsible for developing AI-driven innovative analytical solutions and identifying opportunities to support business and client needs in a quantitative and scalable manner, facilitating informed recommendations and decisions. Activities include designing and deploying machine learning models, building intelligent systems, conducting performance analyses, ad hoc reporting, and AI-powered data visualizations.
In this position, you will:
Lead complex initiatives and projects to derive insights and automation from AI models and systems to solve critical business questions
Translate client/stakeholder needs into AI-driven technical 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 AI applications
Deliver high-quality AI solutions and tools within agreed-upon timelines and budget parameters and conducting post-implementation reviews
Guide others to develop sophisticated AI models and engineering solutions (e.g., intelligent agents, recommendation engines, prototypes) utilizing advanced machine learning, deep learning, and generative AI 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 develops technical talent via ongoing technical training, peer review, and mentorship
All about you:
Proven experience leading AI/ML projects from concept to production
Strong proficiency in Python, Tensor Flow, Py Torch, and cloud platforms (e.g., AWS, Azure, GCP)
Deep understanding of machine learning, deep learning, NLP, and MLOps
Experience with complex neural network architectures and transformer-based models (e.g., BERT, GPT, Vi Ts) is strongly preferred
Experience with data architecture, model deployment, and performance tuning
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 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:
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Abide by Mastercard’s security policies and practices;
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Ensure the confidentiality and integrity of the information being accessed;
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Report any suspected information security violation or breach, and
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Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
Required skills
Machine learning
AI engineering
Model deployment
Leadership
Data analysis
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About Mastercard

Mastercard
PublicA financial network that processes payments between banks and cardholders
10,001+
Employees
Purchase
Headquarters
$360B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
2.8
Compensation
4.1
Culture
4.2
Career
3.4
Management
3.1
72%
Recommend to a friend
Pros
Great team culture and supportive colleagues
Excellent benefits and compensation
Training and development opportunities
Cons
Work-life balance challenges and long hours
High pressure and stress during peak times
Management issues and lack of direction
Salary Ranges
51 data points
L6
L7
L9
Mid/L4
Director
L5
L6 ·
0 reports
$198,500
total per year
Base
-
Stock
-
Bonus
-
$168,725
$228,275
Interview experience
3 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Offer rate
33%
Experience
Positive 33%
Neutral 34%
Negative 33%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Super Day/Final Round
6
Offer
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Past Experience
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