Florian Leibert

Mesosphere, Inc.

San Francisco Bay Area
Computer Software

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Florian Leibert's Overview

  • Advisor at Changemakrs.com
  • Advisor and friend of the firm at Shop O Lot

500+ connections


Florian Leibert's Summary

Building the Mesos company. We're hiring Scala & C++ Engineers who want to be part of an early stage startup.

Software engineer with 15+ years of experience. Founded company at age 16.

Extensive work (both R&D and production environments) in (distributed) data structures, Hadoop (map/reduce) , algorithm design, predictive modeling, lexical semantics, ontology generation / ontology based distance metrics, clustering, recommendation engines.

Developed everything from mobile applications (performance critical) to large scale number crunching algorithms that run on hundreds of cores. Designed and implemented applications such as mobile payment systems, item-to-item recommendation algorithms, novel approach to guarantee fair bandwidth allocation (QoS using unused IP header flags), unstructured text to RDF converters (incl. scraping, segmenting, parsing, pos tagging, semantic analysis), ontology generation and visualization tools, visualization of raw satellite data from the sun - and a myriad of other projects and applications.

Helped scale Airbnb and Twitter.

Florian Leibert's Experience

May 2013Present (1 year 5 months) San Francisco Bay Area



August 2014Present (2 months)

Equity Partner

Data Collective

December 2011Present (2 years 10 months) San Francisco Bay Area



July 2012Present (2 years 3 months) San Francisco Bay Area

Advisor and friend of the firm

Shop O Lot

December 2012Present (1 year 10 months) San Francisco Bay Area

Florian Leibert's Publications

  • Automatic Management of Partitioned, Replicated Search Services

    • Proceedings of the 2nd ACM Symposium on Cloud Computing
    • October 1, 2011
    Authors: Florian Leibert, Jake Mannix, Jimmy Lin, Babak Hamadani

    Low-latency, high-throughput web services are typically achieved through partitioning, replication, and caching. Although these strategies and the general design of large-scale distributed search systems are well known, the academic literature provides surprisingly few details on deployment and operational considerations in production environments. In this paper, we address this gap by sharing the distributed search architecture that underlies Twitter user search, a service for discovering relevant accounts on the popular microblogging service. Our design makes use of the principle that eliminates the distinction between failure and other anticipated service disruptions: as a result, most operational scenarios share exactly the same code path. This simplicity leads to greater robustness and fault-tolerance. Another salient feature of our architecture is its exclusive reliance on open-source software components, which makes it easier for the community to learn from our experiences and replicate our findings.

Florian Leibert's Skills & Expertise

  1. Hadoop
  2. Distributed Systems
  3. Java
  4. Big Data
  5. MapReduce
  6. Data Analysis
  7. Data Mining
  8. System Architecture
  9. Mesos
  10. Natural Language Processing
  11. Search
  12. Network Programming
  13. Apache Pig
  14. Pig
  15. HBase
  16. Microsoft Word
  17. German Law

Florian Leibert's Additional Information

Honors and Awards:

Filed 5 patent applications: three granted, and one pending
Published book: "A Service-Oriented Architecture for Social Networks", published in 2008 by VDM (ISBN: 3639061632)
Various white-papers
Various talks about distributed computing, Hadoop and data mining
Lead in several open source projects, such as DJOP and DNSBalancer

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