Ray Meetup hosted by Adyen: Building and Training Smarter AI with Ray
- Date
- 2025-11-11
- Location
- Amsterdam, Noord-Holland, Netherlands
- Host
- Anyscale
About this event
If you’re building with AI and want systems that are faster to train, easier to scale, and more practical to run in the real world, this meetup is worth your evening. Hosted by Adyen in Amsterdam, this in-person Ray Meetup brings together people working across AI, autonomy, and modern ML infrastructure to talk about how Ray helps teams build and train smarter AI systems. This is a community-first event for people who care about applied machine learning, distributed computing, and the engineering decisions that turn promising models into reliable products. Expect a room full of practitioners, technical conversations that go beyond surface-level trends, and plenty of space to meet others working through similar challenges. About the Event Ray has become an important tool for teams building scalable AI and machine learning workflows, especially when training, orchestration, distributed workloads, and experimentation need to work together without unnecessary complexity. This meetup is centered on that practical reality: how people are using Ray to make AI development more efficient, more flexible, and more production-ready. Hosted by Adyen, the event is designed as an in-person gathering for the local and visiting AI community in Amsterdam. Rather than a broad, vague conversation about the future of AI, the focus here is on the real work of building and training smarter systems: the tools, tradeoffs, patterns, and lessons that matter when systems need to perform outside a demo environment. Because this is a meetup, the format is also part of the value. You’re not just showing up to sit quietly through a sequence of slides. You’re coming into a space where engineers, researchers, builders, and technically curious operators can exchange ideas, compare notes, and build relationships with others doing hands-on work in the field. What to Expect You can expect a structured evening with a mix of technical content and community interaction. The emphasis is likely to be on practical insights around Ray and its role in modern AI workflows, especially in contexts where training, scaling, and orchestration need to work reliably. The evening may include elements like: Welcome and introductions to set the context for the meetup and the themes of the night Talks or presentations focused on building and training AI systems with Ray Real-world perspectives on infrastructure, experimentation, scaling, and workflow design Community discussion where attendees can ask questions and exchange implementation ideas Networking time to meet other people working in AI, ML engineering, autonomy, and related areas Because the event is hosted in person, one of the biggest benefits is the quality of conversation that happens between sessions and after the formal agenda. You’ll have the chance to talk directly with other attendees about the problems you’re trying to solve, whether that’s training efficiency, distributed workloads, model iteration, or team-level workflow challenges. If you’re evaluating Ray, already using it, or simply trying to understand where it fits within the broader AI tooling landscape, this meetup should give you a grounded view through real discussions rather than abstract positioning. Why Attend AI tooling changes quickly, but the underlying questions stay consistent: how do you train faster, scale cleanly, keep systems manageable, and support experimentation without breaking everything around it? This meetup is valuable because it sits right at that intersection of infrastructure, applied ML, and community knowledge-sharing. You’ll come away with a clearer sense of how Ray can support smarter AI development, especially if you’re thinking about distributed training, orchestration, performance, or the practical architecture behind ambitious AI systems. Just as importantly, you’ll hear how other people are approaching similar challenges and where they’ve found leverage. This event is also a strong fit if you value meeting people who are serious about the work. Amsterdam has a deep technical community, and in-person meetups like this create a more useful kind of connection than passive online browsing. Conversations here can lead to better technical decisions, new collaborators, fresh ideas, or simply a more informed view of the current ecosystem. Whether you’re deep in implementation or still exploring the right stack for your next AI project, attending gives you a concentrated way to learn, compare approaches, and stay close to what practitioners are actually doing. Practical Details This is an in-person event in Amsterdam, Netherlands, hosted by Adyen. If you’re based locally, it’s an easy way to plug into the AI and machine learning community in the city. If you’re visiting or working nearby, it’s a strong opportunity to spend an evening with people focused on the technical side of AI development. The meetup takes place on Tuesday, November 11 at 5:30 PM GMT+1. The early evening timing makes it well suited for professionals, founders, engineers, and researchers who want to attend after the workday and still have time for meaningful conversation. A few good reasons to plan ahead: Arrive on time so you don’t miss the opening context and early introductions Come ready to talk shop if you want the most value from the networking side of the event Bring your questions about Ray, training workflows, distributed systems, or practical AI deployment Expect an in-person community setting, not just a one-way presentation format If your work touches AI systems and you want sharper technical conversations than you’ll find in a generic meetup, this is exactly the kind of room you want to be in.
Who should attend
If your work sits anywhere between machine learning, infrastructure, and applied AI, this meetup is likely a strong fit. - You’re an **ML engineer, data scientist, or AI engineer** who wants better ways to train, scale, or orchestrate models and workflows. - You’re a **software or platform engineer** supporting AI workloads and want a clearer understanding of how Ray fits into distributed systems and production environments. - You’re building in **autonomy, intelligent systems, or AI-driven products** and need tooling that can support experimentation without slowing your team down. - You’re a **technical founder, product-minded builder, or engineering lead** evaluating infrastructure choices for smarter, more scalable AI development. - You already use Ray, are considering it, or are simply **curious about practical ML infrastructure** and want to learn from real conversations instead of marketing material. - You value **in-person technical community** and want to meet others in Amsterdam who are actively building, training, and deploying AI systems. If you want concrete insight, thoughtful discussion, and a room full of people working on real AI problems, you’ll feel at home here.