Senior AI Engineer

Mastercard
Dublin
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Collaboration","Communication","Growth mindset","Problem-solving"]

Design, build, and deploy production-ready AI and machine learning solutions that address defined business and product problems. Develop and optimize transformer-based and generative AI models, including fine-tuning, evaluation, and inference workflows, while building data pipelines and feature engineering logic. Implement model serving and MLOps practices such as experiment tracking, versioning, monitoring, and testing, and collaborate with product, data, and engineering partners to deliver reliable AI systems.

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FursaFursa
Mastercard
Mastercard
2 months ago

Senior AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Status: Live
Reposted: similar role first listed 4 months ago

Job Summary

Design, build, and deploy production-ready AI and machine learning solutions that address defined business and product problems. Develop and optimize transformer-based and generative AI models, including fine-tuning, evaluation, and inference workflows, while building data pipelines and feature engineering logic. Implement model serving and MLOps practices such as experiment tracking, versioning, monitoring, and testing, and collaborate with product, data, and engineering partners to deliver reliable AI systems.
Location: Dublin
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Design, develop, and deploy AI and machine learning models to solve defined business and product problems.
  • •Optimize transformer-based and generative AI models, including fine-tuning, evaluation, and inference workflows.
  • •Build and maintain data pipelines, feature engineering logic, and training workflows with data engineering teams.
  • •Implement model serving and inference solutions, integrating models into downstream applications and APIs.
  • •Operationalize MLOps best practices including experiment tracking, versioning, automated testing, monitoring, and performance evaluation.

Key Requirements

  • •Solid experience developing machine learning or AI solutions and deploying them into production environments.
  • •Strong proficiency in Python and experience with ML frameworks such as PyTorch and/or TensorFlow.
  • •Hands-on experience with transformer-based models (e.g., BERT-style encoders, generative models, embeddings).
  • •Experience building data pipelines and managing datasets, including data preparation, feature engineering, and training data workflows.
  • •Working knowledge of MLOps practices, including model deployment, monitoring, and lifecycle management.
Experience:Machine learningAIMLOpsData pipelines
Education:Bachelor's
Skills:CollaborationCommunicationGrowth mindsetProblem-solving
Tech Stack:PythonPyTorchTensorFlowTransformer-based modelsBERTGenerative AIEmbeddingsAWSAzureGCPMLOpsExperiment trackingVersioningAutomated testingMonitoringAPIs

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
Glassdoor: 4.1
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