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Lead AI/ML Feature Engineer

Yesterday London, United Kingdom

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/ML Feature Engineer

Position Overview

As a Lead AI/ML Feature Engineer, you will be at the forefront of designing, developing, and deploying cutting-edge machine learning features that drive core business value for Mastercard. You will leverage your deep technical expertise to build sophisticated data pipelines and engineer impactful features, directly influencing our products and strategies

Key Responsibilities

Design, develop, and implement advanced features from raw data for various machine learning models, ensuring their relevance, robustness, and scalability

Build and optimize efficient and reliable data pipelines to support the ingestion, transformation, and delivery of data for AI/ML applications

Provide technical guidance and mentorship to other junior engineers

Work closely with AI engineers, product managers, and other engineering teams to understand requirements, translate business problems into technical solutions, and integrate AI/ML features into production systems

Support the deployment, monitoring, and maintenance of AI/ML features in production environments

Implement robust testing and validation processes to ensure the quality, accuracy, and reliability of engineered features and AI/ML data pipelines

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Qualifications

Education: Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field

Experience: Minimum of 8+ years of experience in AI/ML feature engineering, data engineering, or a related field, with a strong focus on building and deploying AI/ML feature pipelines in production

Technical Skills:

Proficiency in programming languages such as Python, Scala, or Java

Extensive experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Spark).

Hands-on experience with any of the cloud platforms

Strong background in SQL and NoSQL databases

Experience with big data technologies

Familiarity with MLOps practices and tools (e.g., Docker, Kubernetes, CI/CD for ML)

Exceptional analytical and problem-solving skills, with the ability to translate complex business challenges into technical solutions

Excellent communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders

Proven ability to work effectively in cross-functional teams and drive projects to successful completion

A strong passion for innovation and a track record of exploring and adopting new technologies and methodologies in the AI/ML space

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.

Client-provided location(s): London, United Kingdom
Job ID: Mastercard-22331_R-257252
Employment Type: OTHER
Posted: 2025-08-13T01:42:41

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)