Jobs / Canada / Mastercard International Incorporated

Mastercard International Incorporated

Senior AI Engineer, Big Data & AI Solutions

Vancouver, Canada Posted today

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Skills this job asks for

Machine learningData engineeringPythonSparkSQLAirflowLinuxDeep learningCI/CDCybersecurityRisk managementLLMs

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No sponsorship evidence yet

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  • Confirmed live todayWhen a source last listed this job as open.
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No salary bar for this route
Canada has no single salary bar: the employer usually needs a positive LMIA. Pay at or above the provincial median wage + 20% (e.g. C$36.92/h in Ontario) puts it in the high-wage stream. Source: https://www.canada.ca/en/employment-social-development/services/foreign-workers/median-wage.html, rules effective 2026-07-17.

Canada: Express Entry no longer awards ranking points for job offers (since 25 Mar 2025); a job offer still counts toward Federal Skilled Worker eligibility.

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Sponsorship unknown

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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 Senior AI Engineer, Big Data & AI Solutions 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 The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard's Safety Net product, the team creates and enhances models that analyze billions of transactions and identify suspicious activity in real time. As a Senior AI Engineer, you will work at the intersection of AI engineering and big data engineering, helping improve the models, data assets, and operational processes that power fraud detection. You will collaborate closely with Data Scientists and Engineers to strengthen feature engineering, advance model monitoring capabilities, and deliver AI-driven solutions that improve performance and efficiency.  Role As a Senior AI Engineer, you will: • Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence. • Create data pipelines and feature engineering workflows that enable model development and evaluation. • Process and analyze large-scale datasets to uncover insights and improve model inputs. • Strengthen monitoring, observability, and drift detection capabilities across production environments. • Apply automation and MLOps practices to improve reliability, efficiency, and scalability. • Develop AI-powered solutions that address engineering challenges and streamline operational processes. -Partner with Data Scientists, Engineers, and Product teams to bring new capabilities into production. • Contribute ideas that improve model performance, operational visibility, and team productivity. Required Qualifications • Master’s degree with relevant experience, or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered. • Proficiency in Python, PySpark, SQL, and distributed data processing. • Hands-on experience with feature engineering, large-scale data processing, and analytics. • Hands-on experience with Databricks, Airflow, Hadoop, Linux/Unix, cloud-native technologies • Understanding of machine learning and deep learning techniques. • Understanding of model deployment, evaluation, monitoring, and optimization. • Knowledge of MLOps concepts including testing, automation, CI/CD, and version control. • Ability to communicate technical concepts and collaborate across teams. Preferred Qualifications • Fraud, cybersecurity, payments, or risk management domains. • Experience with Generat

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