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Senior Machine Learning Engineer - AI

Geplaatst 9 aug. 2026
Delen:
Werkervaring
7 tot 12 jaar
Full-time / part-time
Full-time
Functie
Opleidingsniveau
Taalvereiste
Engels (Vloeiend)

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Senior Machine Learning Engineer (AI) - Payments

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft. Our Payment Solutions team processes billions of transactions while empowering businesses to create seamless payment experiences. As Adyen and our merchants scale globally, the complexity and volume of operational knowledge are growing exponentially.

To position our Payments organization at the technological forefront, we are establishing a GenAI team focused on identifying high-impact use cases for automation through agentic capabilities. As a Senior Machine Learning Engineer - AI, you will undertake technically demanding work in applied AI: designing agents that reason over complex, multi-step tasks, building infrastructure to ensure production-grade reliability, and shaping how humans and AI collaborate at scale within a global payments company.

This is not a narrow research role. You will take full ownership of your work, from early research through deployed production systems, influence the team's technical direction, and act as a force multiplier for the broader AI organization, including contributing to custom model development for structured financial data and working toward defining how humans and AI collaborate at scale across the company.

What you’ll do:

  • Discover and build: proactively engage with product and engineering teams to uncover critical challenges, identify high-impact opportunities, and rapidly design and build AI prototypes (MVPs) to demonstrate value.
  • Develop strategic AI products: own the end-to-end development of bespoke AI tools that solve problems unique to Adyen's scale, including optimizing merchant experience, enhancing pricing models, and improving internal workflows.
  • Own evaluation and benchmarking: define and lead the evaluation strategy for agentic systems and LLMs, design internal benchmarks grounded in real domain complexity, and build reusable evaluation infrastructure embedded in the development process.
  • Provide AI expertise across the organization: serve as a technical resource for AI initiatives across Adyen, evaluating agentic frameworks, retrieval and search strategies, and agent tool-use approaches across partner teams.
  • Raise the bar: set engineering standards for the team and company, provide mentorship through problem decomposition, research methodology, and code review, and champion reproducibility, documentation, and rigorous evaluation practices.

Who you are:

  • You have 7+ years of hands-on experience in applied AI/ML research or engineering, with a track record of shipping AI systems, including agentic or LLM-powered systems, in production environments.
  • You have deep expertise in language models and Generative AI, with hands-on depth across several of: architecture, post-training (fine-tuning, RLHF), inference optimization, context engineering (RAG), and failure modes at scale.
  • You have proven experience designing and operating agentic systems at scale, including multi-agent orchestration, tool use, memory and context management, state handling for long-running workflows, and human-in-the-loop design.
  • You are rigorous and systematic about evaluation and have designed evaluation frameworks or internal benchmarks that go beyond standard metrics.
  • You have a strong foundation in classical machine learning: supervised learning, ensemble methods, optimization, probabilistic modeling, and statistics.
  • You write clean, well-structured, production-ready code, primarily Python, and hold research code to an engineering standard.
  • You have hands-on experience with at least one production-grade agentic framework.

Nice to have:

  • Familiarity with financial data, payments, fraud detection, or risk systems.
  • Track record of external visibility: publications, conference presentations, or open-source contributions.
  • Experience with observability and evaluation tooling.
  • Familiarity with MLOps and model deployment pipelines in large-scale environments.

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.

We took an unobvious approach to starting a payments company, building a platform from scratch. Today, we're the payments platform of choice for the world's brightest companies. Our unobvious approach is a product of our diverse perspectives. This diversity, of backgrounds, cultures, and perspectives, is essential in helping us maintain our momentum.

Financieel & Banken
Amsterdam
Actief in 22 landen
1.700 medewerkers
60% mannen - 40% vrouwen
Gemiddeld 31 jaar oud