Software Engineer II - ML / AI

Requirements:

• You have 3-6 years of hands-on experience in applied AI/ML research or engineering, with a clear 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, multi-agent orchestration, tool use, memory and context management, state handling for long-running workflows, and human-in-the-loop design. You understand what separates production agents from research prototypes.
• You are rigorous and systematic about evaluation. You have designed evaluation frameworks or internal benchmarks that go beyond standard metrics. You understand the failure modes of LLM-as-judge approaches and know how to measure what actually matters for a given system and use-case.
• You have a strong foundation in classical machine learning: supervised learning, ensemble methods, optimization, probabilistic modeling, and statistics. You reach for the appropriate tool for the problem.
• You write clean, well-structured, production-ready code, primarily Python, and you hold research code to an engineering standard.
• You have hands-on experience with at least one production-grade agentic framework.

What you'll be doing:

• Discover and Build: You will be an explorer within Adyen, proactively engaging with product and engineering teams to uncover their most critical challenges. You won't wait for instructions; you'll find high-impact opportunities and rapidly design and build AI prototypes (MVPs) to demonstrate value.
• Develop Strategic AI Products: You will own the end-to-end development of bespoke AI tools that solve problems unique to Adyen's scale. Whether it's optimizing merchant experience, enhancing pricing models, or improving internal workflows, you will build intelligent solutions.
• Own Evaluation and Benchmarking: Define and lead the evaluation strategy for the agentic systems and LLMs your team builds and deploys. Design internal benchmarks grounded in real domain complexity, probing for genuine capabilities, edge cases, and failure modes that standard metrics miss. Build reusable evaluation infrastructure that is embedded in the development process, not bolted on after the fact.
• Provide AI Expertise Across the Organization: Serve as a technical resource for AI initiatives across Adyen - evaluating agentic frameworks, retrieval and search strategies, or agent tool-use approaches across partner teams. Surface connections across initiatives and help teams avoid duplicating work or converging on the wrong approach.
• Raise the Bar: Set engineering standards for the team and company. Provide mentorship through problem decomposition, research methodology, and code review. Champion reproducibility, documentation, and rigorous evaluation practices across the AI organization.

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.

Perks and Benefits:

• Our unique approach is a product of our diverse perspectives, welcoming all backgrounds.
• Encouraging applicants from underrepresented communities to apply even if they meet most but not all qualifications.
• Smooth and enjoyable candidate experience with a response within 5 business days and an interview process of about 4 weeks.