Mastercard

1 day ago

Lead AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Design, develop, and scale AI and machine learning platforms, data pipelines, and infrastructure that power Identity Verification products. Work on large-scale distributed data processing, automate and optimize ML workflows, and improve platform reliability, scalability, performance, observability, and operational excellence. Lead technical design reviews and provide technical leadership to enable Data Science teams to deliver reliable, production-ready AI solutions in a cross-team environment.

Location: Budapest

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build and maintain data pipelines, machine learning infrastructure, and platform capabilities for Data Science solutions across Identity Verification products.
•Design complex, scalable, maintainable, and efficient ML platform systems and automations for ML workflows and engineering processes.
•Drive improvements in platform reliability, scalability, performance, observability, and operational excellence.
•Own code performance and automated testing, and ensure CI/CD and infrastructure automation practices are followed.
•Provide technical leadership through design reviews, architecture discussions, solution development, and cross-team collaboration; mentor engineers.

Key Requirements

•Relevant senior or lead-level experience in software, data, or AI engineering.
•Strong programming skills in Python and experience with Java, Scala, or similar languages.
•Experience with large-scale distributed data processing platforms or big data query engines, preferably Apache Spark.
•Experience designing, building, and operating large-scale data platforms and supporting machine learning systems in production.
•Strong understanding of machine learning concepts (feature engineering, training, deployment, and monitoring) and cloud-native architectures (AWS preferred).

Experience:Machine learningBig dataDistributed systemsProduction AI

Skills:Technical leadershipCommunicationCollaborationMentoringContinuous improvement

Tech Stack:PythonJavaScalaApache SparkDatabricksAWSJiraConfluence

Company Brief

Mastercard

Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Mastercard

1 day ago

Lead AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: Budapest

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build and maintain data pipelines, machine learning infrastructure, and platform capabilities for Data Science solutions across Identity Verification products.
•Design complex, scalable, maintainable, and efficient ML platform systems and automations for ML workflows and engineering processes.
•Drive improvements in platform reliability, scalability, performance, observability, and operational excellence.
•Own code performance and automated testing, and ensure CI/CD and infrastructure automation practices are followed.
•Provide technical leadership through design reviews, architecture discussions, solution development, and cross-team collaboration; mentor engineers.

Key Requirements

•Relevant senior or lead-level experience in software, data, or AI engineering.
•Strong programming skills in Python and experience with Java, Scala, or similar languages.
•Experience with large-scale distributed data processing platforms or big data query engines, preferably Apache Spark.
•Experience designing, building, and operating large-scale data platforms and supporting machine learning systems in production.
•Strong understanding of machine learning concepts (feature engineering, training, deployment, and monitoring) and cloud-native architectures (AWS preferred).

Experience:Machine learningBig dataDistributed systemsProduction AI

Skills:Technical leadershipCommunicationCollaborationMentoringContinuous improvement

Tech Stack:PythonJavaScalaApache SparkDatabricksAWSJiraConfluence

Company Brief

Mastercard

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor