Ray x MLOps Community Meetup: Scaling Multi-Modal Data & Batch Inference
Modern AI workloads are more complex than ever from handling multi-modal data to serving large models at scale. Join us to see how teams are using Ray to simplify distributed training, streamline data processing, and power production-grade batch and online inference, all in one unified platform.
This Ray x MLOps Munich Meetup brings together practitioners from Synthesia and Anyscale for an evening of technical talks, demos, and community networking. You'll learn how to scale AI systems, plus get a firsthand look at how Ray is being used in real-world production environments.
Agenda:
[6:30pm - 7:00pm] Welcome & Networking
[7:00pm - 8:00pm] Technical talks:
1. Introduction to Ray and Anyscale - Distributed Training by Ali Sezer, Field Engineering Lead, Anyscale
2. Playbook for Training Large Models by Ali Abbas Jaffri, ML Platform Engineer @ Synthesia
Training large models efficiently on public cloud platforms like AWS and GCP requires more than just powerful GPUs; it demands a well-orchestrated infrastructure pipeline. This talk briefly touches the avenues of end-to-end process of preparing and managing large-scale training environments, from dataset curation and preprocessing to distributed training and observability.
3. Production Grade Online Inference by Ali Sezer, Field Engineering Lead, Anyscale
4. Q&A
[8:00pm - 8:30pm] Q&A and Networking
Whether you're experimenting with Ray for the first time or already deploying large-scale AI systems in production, this is a great opportunity to connect with the local MLOps community, exchange ideas, and learn from others who are scaling smarter with Ray.
We can't wait to see you there!
About Anyscale
Anyscale, the company behind Ray open source, is a fully-managed, enterprise-ready unified AI platform. With Anyscale, companies can build, deploy, and manage all their AI use cases, bringing transformational AI products to market faster.
Try it for free here.
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