Senior AI Engineer

Reposted 3 Days Ago
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Gurugram, Haryana, IND
Hybrid
Senior level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
The Senior AI Engineer will architect, develop, and deploy AI/ML solutions for product optimization and sales, ensuring governance and operational excellence.
Summary Generated by Built In
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 AI Engineer
Who is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.Overview (Our Team)
As consumer preference for digital payments continues to grow, ensuring a seamless and secure consumer experience is top of mind. The Optimization Solutions team focuses on tracking digital performance across products and regions, understanding factors influencing performance and the broader industry landscape, and delivering data-driven insights and recommendations. We engage directly with key stakeholders to implement optimization solutions (new and existing) and partner across the organization to drive alignment and action.
If you're excited about data assets, passionate about data-driven decision-making, and want to build large-scale analytical capabilities used across global markets, this is the role for you.The Role
As a Senior AI Engineer, you will architect, develop, and deploy AI/ML solutions that generate actionable insights for product optimization and sales enablement. You will work with global stakeholders across geographies, develop reusable and scalable models, and partner with engineering teams to productionize AI capabilities.
This role emphasizes end-to-end ownership: problem definition → data & feature pipelines → modelling → evaluation → deployment → monitoring & iteration-with strong attention to governance, privacy, and operational excellence aligned to Mastercard standards. Key Responsibilities
AI/ML Solution Development & Innovation• Architect, build, and maintain AI/ML systems to solve business problems, including predictive modelling and decisioning solutions for optimization use cases• Prototype new algorithms, run experiments, evaluate performance against agreed metrics, and deliver production-ready insights and models• Translate ambiguous business challenges into measurable ML objectives; simplify complex technical requirements to align with stakeholder needs.
Data Engineering Foundations for AI• Perform data ingestion, aggregation, processing, and feature engineering on high-volume, high-dimensional datasets to enable reliable training and inference• Apply benchmarking, measurement, and metric design to validate model impact and support decision-making.
Reusable & Scalable AI (Patterns + Microservices)• Identify common use-case patterns and promote scalable AI delivery via reusable models, shared components, and a microservice approach.• Drive the evolution of AI-enabled products by improving model robustness, latency, and maintainability.
Productionization, MLOps & Operational Excellence• Deploy models into production in partnership with technical teams; design scalable training/inference pipelines and deployment frameworks• Automate training, testing, deployment, and updates using CI/CD best practices; manage model versioning and performance monitoring (drift, quality, reliability
Governance, Privacy & Responsible AI• Ensure AI solutions follow industry standards and Mastercard practices for data management and privacy-covering data collection, storage, access, retention, outputs/reporting, and quality.• Contribute to ethical AI practices and robust AI infrastructure to support reliable production operations
Collaboration & Leadership• Collaborate with global stakeholders to gather information, define business problems, and deliver outcomes across teams and geographies.• Mentor and guide junior team members, fostering a culture of learning and continuous improvement. All About You (Required Qualifications)• 5+ years of experience in Data Science / AI / Machine Learning, including strategy, execution, and solution development from the ground up.• Strong hands-on expertise with:
o Python (preferred), R, and SQL; proficiency with statistical and ML development workflows.
o Classical ML methods (e.g., Logistic Regression, Decision Trees, K-Means, PCA, Time Series models such as ARIMA/ARMA).
o Advanced ML / DL approaches (e.g., Gradient Boosting/GBM, Neural Networks including CNN/LSTM; optimization methods such as Adam/Adagrad).
o Production frameworks: TensorFlow, Keras, PyTorch, XGBoost.• Experience working with big data and scalable compute (e.g., Hadoop/Hive/Spark, GPU-enabled environments).• Demonstrated practical AI mindset: ability to simplify complexity, make tradeoffs, and deliver business-aligned outcomes.• Excellent written and verbal communication skills; ability to influence and partner across disciplines.• Computer Science (or closely related) background.
Effectiveness / What Success Looks Like• Strong problem-solving: break down complex problems, select the right AI techniques, and deliver confidently validated solutions.• Ability to manage assumptions and validate them with stakeholders under tight deadlines while keeping delivery on track.• Deep attention to detail and a high bar for quality, reproducibility, and operational reliability.• Strong architectural thinking: anticipate system interdependencies, constraints, and production challenges proactively. Core Capabilities• Clear communicator who can bridge technical and non-technical audiences.• Strong project management and stakeholder management skills.• Team-first mindset; effective in global, cross-functional collaboration.
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.

Skills Required

  • 5+ years of experience in Data Science / AI / Machine Learning
  • Strong hands-on expertise with Python (preferred), R, and SQL
  • Proficiency with statistical and ML development workflows
  • Experience with big data and scalable compute (e.g. Hadoop/Hive/Spark, GPU-enabled environments)
  • Computer Science (or closely related) background

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support Retirement programs include an employer match up to 10% (401k or local equivalent), consistently highlighted in careers materials. Feedback suggests this is a standout component of total rewards.
  • Parental & Family Support A global minimum of 16 weeks paid new‑parent leave is offered for birth, adoption, or foster placements, with financial assistance for fertility, adoption, and surrogacy where allowed. Feedback suggests these provisions are robust relative to many large employers.
  • Flexible Benefits Flexibility features include hybrid work, a four‑week “work from elsewhere” program, quarterly meeting‑free days, and five paid volunteer days. Feedback suggests these options support work/life balance across many roles.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

Typical time on-site: 3 days a week
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