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Senior AI Research Engineer

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Adyen

Adyen is a financial technology company providing a unified platform for payments, data, and financial products. It serves global enterprises, retailers, platforms, marketplaces, and other high-growth businesses.

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About Adyen

Adyen provides payment processing and financial technology services through a single platform. Its offerings include online and in-person payments, payment methods, risk management, authentication, revenue optimization, issuing, payouts, liquidity management, embedded accounts, and capital. Adyen typically serves global enterprises, retailers, SaaS platforms, marketplaces, and other high-growth businesses.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You explore and apply cutting-edge AI research in finance, implement research papers as production-quality code, develop scalable generative AI applications, and help shape AI strategy. You mentor engineers, solve complex technical problems, communicate research clearly, and connect with the broader AI community.

Requirements

  • Strong understanding of current AI research advancements
  • Significant experience with Generative AI and Large Language Models
  • Track record of writing clean, efficient, and scalable production code
  • Experience implementing cutting-edge AI research papers into production-quality code
  • Ability to solve complex cross-team problems
  • Ability to communicate complex technical concepts to diverse audiences
  • Experience with product thinking, AI use cases, classical machine learning, external visibility activities, or on-premises infrastructure is advantageous

Responsibilities

  • Drive practical applications of Generative AI and other AI methodologies in finance
  • Implement research papers into robust, scalable, production-ready code
  • Contribute to AI strategy and long-term vision
  • Address regulation and promote safe AI innovation
  • Develop creative solutions to real-world problems
  • Mentor engineers and share knowledge and best practices
  • Pair with engineering teams on technical challenges
  • Create proof-of-concepts and resolve performance issues
  • Engage with startups, venture capital firms, and AI labs