Daniil Mazepin

Daniil Mazepin

Engineering Manager at CoreWeave

London, United Kingdom

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I work as a Senior Engineering Manager on CoreWeave's Physical AI team, leading engineering teams building the systems that train and deploy AI for the physical world - robotics, autonomous systems, and industrial applications. Previously I operated distributed backend systems at hyperscale at Meta and led payments infrastructure at Teya, a UK fintech unicorn serving 75,000+ European merchants, with earlier roles at Playtech. I work at intersection of large-scale distributed systems, ML infrastructure, and engineering leadership. My experience spans multiple domains including fintech, social media, e-commerce, and gambling, utilising both top-down and bottom-up approaches.
Also I am established speaker at industry events and conferences across Europe (Ukraine, Portugal, UK), based in London.

Area of Expertise

  • Business & Management
  • Consumer Goods & Services
  • Finance & Banking
  • Information & Communications Technology

Topics

  • AI Infrastructure
  • Cloud & AI Infrastructure
  • AI Infrastructure Strategy & Economics
  • MLOps & AI Infrastructure
  • ML/AI Infrastructure
  • AI infrastructureGPU scheduling
  • AI Infrastructure & Cloud Native AI
  • Cloud-Native AI Infrastructure
  • Responsible AI Infrastructure
  • Scalability Engineering
  • High Availability and Scalability
  • Software Architecture & Scalability
  • Scalability and Performance
  • scalability and reliability
  • Scalability and Load Balancing
  • Scalability & Growth Strategy
  • Scalability & Performance Engineering
  • Scalability in distributed financial systems
  • Infrastructure and scalability
  • Data Platform Scalability
  • Reliability
  • Reliability Engineering
  • Data reliability
  • Software Reliability
  • AI Reliability Engineering
  • Service Reliability Engineering
  • Service Reliability Architecture
  • DevOps & Site Reliability Engineering
  • Site reliability engineering (SRE) in fintech
  • Reliability services
  • Reliability Engineering (SRE)
  • Site Reliability Engineering (SRE)
  • Scaling Teams
  • The Leader’s Playbook for Scaling Teams and Operations
  • leading technical teams
  • AI Adoption
  • AI Adoption and Implementation
  • Structured AI Adoption
  • Developer Productivity
  • AI & Developer Productivity
  • Measuring developer productivity in the AI era

Overcomplicated solutions: a costly mistake

Some decisions are easy to reverse, while others might take years (and millions) to undo. Let’s take a retrospective look at some of these decisions that literally cost the company much more than the original problem they were meant to solve. Let’s learn from these mistakes and explore what could have been done differently at each step of the project.

How do you determine and measure system availability?

Your reported metric for availability looks good, but users are still complaining? Don’t have enough time in your roadmap to address tech debt issues? Is your upstream dependency down again, affecting your user experience? Do these issues sound familiar to you? Let’s talk about SLOs and how adopting them can help you provide a better user experience for your customers.

Tech Summit

My topic - "Beyond the Fix: Collaboration, Product-First Thinking, and the Price of Wrong Decisions”

November 2024 London, United Kingdom

KCD Porto

"From Concept to Measurement: Practical Approaches to System Availability"

September 2024 Porto, Portugal

The National DevOps Conference

"From Uptime to User Satisfaction: Rethinking System Availability Metrics"

September 2024 London, United Kingdom

London Tech Community

Overcomplicated Solutions: A Costly Mistake

July 2024 London, United Kingdom

Highload fwdays'24

"What does it really mean for your system to be available, or how to define what to measure"

June 2024 Kyiv, Ukraine

Daniil Mazepin

Engineering Manager at CoreWeave

London, United Kingdom

Actions

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