Mastercard

1 month ago

Director of AI Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Lead a specialized AI engineering team building foundation models and delivering high‑value, production‑ready AI use cases. Drive transformer‑based and generative AI capabilities, from problem definition through model integration and deployment, while balancing innovation with reliability, security and governance. Collaborate with product, data engineering and platform teams to translate AI capabilities into measurable business impact.

Location: Dublin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Director level

Key Responsibilities

•Lead a team of AI engineers focused on foundation model development, fine‑tuning, and optimisation, particularly transformer‑based and generative AI systems
•Drive the end‑to‑end delivery of AI use cases, from problem definition through model integration and production deployment
•Partner with product and business stakeholders to identify and prioritise high‑impact AI use cases, translating them into clear technical execution plans
•Ensure effective use of foundation models across use cases, including prompting strategies, embeddings, fine‑tuning, evaluation, and performance optimisation
•Collaborate with data engineering and platform teams to ensure data readiness, model integration, and scalable deployment patterns

Key Requirements

•Proven experience leading teams delivering AI/ML solutions in production, particularly in use‑case driven environments
•Strong hands‑on understanding of transformer architectures and generative AI, including fine‑tuning, prompting, embeddings, and evaluation
•Experience bridging model development and real‑world application, translating AI capabilities into business impact
•Solid engineering background, with familiarity in Python, ML frameworks (e.g. PyTorch/TensorFlow), and production deployment patterns
•Experience working with data engineering and MLOps practices to support training, evaluation, and inference at scale

Experience:AIMachine learningFoundation modelsTransformersGenerative AIMLOps

Skills:PythonPyTorchTensorFlowProduction deploymentData engineeringMLOpsMachine learningAI engineering

Languages:English

Tech Stack:PythonPyTorchTensorFlowMLOpsData EngineeringEmbeddingsFine‑tuningPromptingTransformersGPTProduction deployment

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 month ago

Director of AI Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Dublin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Director level

Key Responsibilities

•Lead a team of AI engineers focused on foundation model development, fine‑tuning, and optimisation, particularly transformer‑based and generative AI systems
•Drive the end‑to‑end delivery of AI use cases, from problem definition through model integration and production deployment
•Partner with product and business stakeholders to identify and prioritise high‑impact AI use cases, translating them into clear technical execution plans
•Ensure effective use of foundation models across use cases, including prompting strategies, embeddings, fine‑tuning, evaluation, and performance optimisation
•Collaborate with data engineering and platform teams to ensure data readiness, model integration, and scalable deployment patterns

Key Requirements

•Proven experience leading teams delivering AI/ML solutions in production, particularly in use‑case driven environments
•Strong hands‑on understanding of transformer architectures and generative AI, including fine‑tuning, prompting, embeddings, and evaluation
•Experience bridging model development and real‑world application, translating AI capabilities into business impact
•Solid engineering background, with familiarity in Python, ML frameworks (e.g. PyTorch/TensorFlow), and production deployment patterns
•Experience working with data engineering and MLOps practices to support training, evaluation, and inference at scale

Experience:AIMachine learningFoundation modelsTransformersGenerative AIMLOps

Skills:PythonPyTorchTensorFlowProduction deploymentData engineeringMLOpsMachine learningAI engineering

Languages:English

Tech Stack:PythonPyTorchTensorFlowMLOpsData EngineeringEmbeddingsFine‑tuningPromptingTransformersGPTProduction deployment

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