Only Until April 16: ✓ Save up to £395  ✓ 10% Team Discount ✓ Parallel Conferences for £250

Only Until April 16: ✓ Save up to £395  ✓ 10% Team Discount ✓ Parallel Conferences for £250

Until Event Starts: ✓ Save up to 249 € ✓ 4-Day Special ✓ 10% Team Discount

Until Event Starts: ✓ Save up to 249 € ✓ 4-Day Special ✓ 10% Team Discount

Only Until April 30: ✓ Save up to $500 ✓ 10% Team Discount ✓ Access to Parallel Conferences for $250

Only Until April 30: ✓ Save up to $500 ✓ 10% Team Discount ✓ Access to Parallel Conferences for $250

Only Until May 7: ✓ Save up to 315€ ✓ 10% Team Discount ✓ Access to devmio

Only Until May 7: ✓ Save up to 315€ ✓ 10% Team Discount ✓ Access to devmio

Only Until June 11: ✓ Save up to $960 ✓ Free Workshop Day ✓ 10% Team Discount

Only Until June 11: ✓ Save up to $960 ✓ Free Workshop Day ✓ 10% Team Discount

Thank you, Berlin MLcon community ✓ 2026 dates soon ✓ Join the community newsletter for exclusive content

Thank you, Berlin MLcon community ✓ 2026 dates soon ✓ Join the community newsletter for exclusive content

From lab to live—operationalize ML and LLMs with confidence

Streamline your ML and LLM deployment lifecycle with reproducible pipelines, CI/CD automation, and secure infrastructure. This track is your roadmap to scaling AI systems securely and reliably.

Speaker Programm Program

MLOps, LLMOps & Pipelines

Learn from Industry Leaders about:

  • CI/CD pipelines for ML & LLM deployment
  • Reproducibility and model versioning with registries
  • Drift monitoring and alerting at scale
  • Infrastructure automation across clouds and clusters
  • Best practices for secure, reliable production AI

Frequently Asked Questions

What is the goal of the MLOps & LLMOps track?

This track teaches how to move models from development to deployment. You’ll master automated CI/CD for ML, drift detection, model versioning, and infrastructure orchestration tailored for both traditional ML and modern LLM workflows.

How is LLMOps different from MLOps?

LLMOps extends MLOps practices to large language models. It focuses on managing prompts, handling scale, monitoring hallucinations, and versioning LLM behaviors—all while ensuring security and consistency.

What tools and platforms are covered?

You’ll work with MLflow, DVC, KServe, Terraform, Helm, and Kubernetes. Each tool is covered in context—helping you build auditable, resilient, and secure AI systems.

How does this track support production-readiness?

By focusing on reproducibility and infrastructure-as-code, this track equips engineers to scale AI while maintaining traceability and compliance. It emphasizes strategies for rollback, drift response, and cross-environment parity.

Track Speakers London 2026

Track Speakers San Diego 2026

San Diego's program will go live soon! Until then, please take a look at

New York's 2024 Program!

Track Speakers Munich 2026

Track Speakers Amsterdam 2026

Track Speakers New York 2025

Track Speakers Berlin 2025

Track Program London 2026

Track Highlights San Diego 2026

MLOps Track Program 2026

Track Program New York 2025

Track Program Berlin 2025

We are currently working on this part of the program. Check back soon and have a look at the rest of the current MLCON Munich 2023 program here.

Track Program Amsterdam 2026