Machine Learning at Scale: Become a x10 Engineer

Machine Learning at Scale

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Type:
Website
Last Updated:
2025/09/04
Description:
Machine Learning at Scale provides insights & resources to become a top Machine Learning Engineer. Deep dives into RAG, LLM optimizations, and ML system design.
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machine learning systems
LLM optimization
RAG
recommendation algorithms
ML system design

Overview of Machine Learning at Scale

Machine Learning at Scale: Your Path to Becoming a x10 Machine Learning Engineer

What is Machine Learning at Scale? Machine Learning at Scale is a resource dedicated to helping machine learning engineers upskill and excel in their careers. It provides weekly, high-quality insights into various aspects of machine learning, with a focus on building and optimizing large-scale ML systems.

Core Focus Areas

  • RAG (Retrieval-Augmented Generation) systems: Deep dives into RAG architectures and their applications.
  • LLM (Large Language Model) optimizations: Strategies and techniques for optimizing the performance and efficiency of LLMs.
  • LLM training: Insights into the process of training large language models.
  • ML System design: Best practices for designing and building robust and scalable machine learning systems.
  • Recommendation systems: Exploration of various recommendation algorithms and their implementation.

Who is Ludo?

Ludo, the creator of Machine Learning at Scale, is a Machine Learning Engineer at Google with extensive experience in building and deploying large-scale ML systems. His background includes:

  • Working with large-scale ML systems to fight abuse across billions of users at 500k QPS.
  • Pretraining and finetuning transformer-based models to understand user behavior.
  • Working with end-to-end YouTube Ads systems from Ads selection to formats.
  • Applying Machine Learning techniques at CERN to understand particle interactions.
  • Developing computer vision thesis based on Transformers at Volvo.

Why is Machine Learning at Scale Important?

In today's rapidly evolving AI landscape, staying ahead of the curve is crucial for machine learning engineers. Machine Learning at Scale provides valuable insights and resources to help engineers:

  • Upskill: Acquire new skills and knowledge in key areas of machine learning.
  • Stay informed: Keep up-to-date with the latest advancements in the field.
  • Build better systems: Design and build more robust and scalable machine learning systems.

How to Get Involved

  • Subscribe: Sign up to receive weekly insights and updates.
  • Contact: Reach out for a free initial consultation if you're a business looking for AI help, specializing in Retrieval, Ranking and Recommendation systems and LLM integrations within those.

Unlock Your Full Potential

Machine Learning at Scale is your resource for becoming a better Machine Learning Engineer.

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