Martin Krasser

I’m a self-employed machine learning engineer and distributed systems specialist with a strong background in software engineering. I have experience with “traditional” machine learning, deep learning and Bayesian methods for machine learning. My deep learning projects mainly focus on computer vision problems but recently also on natural language processing. My distributed systems experience comes from the development of numerous large-scale event-driven systems as well as globally distributed systems that provide causal consistency guarantees. I’m a continuous learner, passionate about technology and contributor to several open source projects.


Distributed systems, data-intensive applications, data science, machine learning, deep learning, system integration, event sourcing and CQRS, event stream processing, event-driven architectures, message-driven architectures, resilience, scalability, high availability, functional programming, object-oriented programming, probabilistic programming.

Work experience

See also Stories for further information.

Since 04.2018, Machine learning engineer (freelancer)


  • Design and implementation of AI extensions for the MerlinOne digital asset management system.
  • Application of deep learning methods for large-scale facial recognition, content-based image retrieval, image aesthetics assessment and single image super-resolution.
  • Responsible for the scientific and engineering parts of all machine learning projects.
  • Support production deployments to several customer sites (hosted and on-premise).

Since 04.2011, Machine learning engineer, software engineer and architect


  • Research and software development in context of industry machine learning projects.
  • Distributed systems development and consulting services.
  • See other positions since 2011 for further details.

05.2017 to 04.2018, Machine learning sabbatical

Sabbatical year

  • Deep dive into statistics, “traditional” machine learning and deep learning.
  • Certifications received in statistics and machine learning MOOCs.
  • Publication of some exercise work in articles and open source projects.
  • Equal focus on theoretical and engineering aspects of machine learning.

02.2017 - 04.2017, Distributed systems engineer (freelancer) GmbH,

  • Design and implementation of a distributed system architecture based on event sourcing with explicit causality that also includes mobile devices.
  • Consulting activities and development of prototypes.

09.2014 - 08.2017, Distributed systems engineer (freelancer)

Red Bull Media House,

  • Global distribution of the in-house digital asset management platform. Responsible for architecture, design and implementation.
  • Conception and development of Eventuate, a toolkit for event sourcing and event collaboration at global scale with causal consistency.

10.2015 - 07.2017, Software engineer and architect (freelancer)

agido GmbH,

  • Architecture and design consulting for an online sports betting web application with an event sourcing and event stream processing architecture.
  • Usage of Eventuate as technical basis for the web application backend. Development of streaming data analytics extensions for Eventuate.

10.2013 – 02.2014, Software engineer and architect (freelancer)

Lightbend, (formerly Typesafe)

03.2012 – 10.2013, Software engineer and architect (freelancer)

Eligotech BV,

  • Development of an E-Wallet management web service for customers in the online gambling industry.
  • Conception and development of Eventsourced, an open source project for building reliable, scalable and distributed event-sourced applications in Scala.

02.2011 – 04.2011, Senior software architect and engineer


  • Development of scalability and high-availability concepts and prototypes for the Talend Integration Factory.

01.2005 – 01.2011, Lead software architect and engineer

InterComponentWare AG,

  • Conception and development of the Open eHealth Integration Platform (IPF), an eHealth integration platform on top of Apache Camel. Development and deployment of IPF applications in several international customer projects.
  • Development of LifeSensor, a web-based personal health record.

09.2000 – 12.2004, Senior software architect and engineer

LION bioscience AG,

  • Development and optimization of hierarchical clustering algorithms for the drug discovery pipeline of an international pharmaceutical company.
  • Development of an integration platform for globally distributed chemical compute services.
  • Development of an activity tracking web application for pharmaceutical research projects.

02.1999 – 08.2000, Software developer, Research assistant

CAME, University of Salzburg,

  • Development of algorithms and software for ab-initio protein structure prediction. Application of statistical mechanics to evaluate generated protein structures.

07.1998 – 01.1999, Software developer

Austrian Red Cross,

  • Development of a patient transportation management system.

Tools experience (excerpt)

  • Programming languages: Scala, Java, Python, C/C++, Haskell.
  • Machine learning: scikit-learn, Tensorflow/Keras, PyTorch, PyMC3, Spark MLlib, R.
  • Databases: MySQL, PostgreSQL, Oracle, Cassandra, HBase, DynamoDB, MongoDB, LMDB, LevelDB, …
  • Stream processing: Spark Streaming, Akka Streams, Kafka Streams.
  • Cloud computing: Amazon Web Services and Google Cloud Platform.
  • Java SE and Java EE stack plus many other Java libraries and frameworks.
  • Lightbend Reactive Platform plus many other Scala libraries and frameworks.
  • Confluent Platform (Apache Kafka and its ecosystem) and Reactive Kafka.

Open source projects

The following is an incomplete list of open source projects I’m currently working on or worked on in the past. See also Stories for some details and my Github account for a complete list.

Machine learning

  • Bayesian machine learning. Collection of notebooks related to Bayesian machine learning. Extended when I’m writing new articles about that topic.
  • Super resolution. Tensorflow 2.0 based implementation of WDSR, EDSR and SRGAN for single image super-resolution.
  • Face recognition. Deep face recognition with Keras, Dlib and OpenCV.
  • Machine learning notebooks. Stanford machine learning course exercises re-written in Python and scikit-learn.

Distributed systems and stream processing

  • Eventuate. A toolkit for event sourcing and event collaboration at global scale with causal consistency. Founder and lead developer during my work at the Red Bull Media House.
  • Streamz. A combinator library for integrating Functional Streams for Scala (FS2), Akka Streams and Apache Camel. Personal project that I’m still actively developing. Functional programming API on top of Apache Camel and successor of Akka Camel.
  • Akka. A toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Contributed Akka Persistence and Akka Camel.
  • akka-persistence-cassandra. Storage plugin for Akka Persistence. Started as personal project and now officially maintained by Lightbend.
  • akka-stream-eventsourcing. Personal project that brings to Akka Streams what Akka Persistence brings to Akka Actors: persistence via event sourcing. This is experimental work, inactive at the moment.
  • Eventsourced. A library for building reliable, scalable and distributed event-sourced applications in Scala. Founder and lead developer during my work at Eligotech. Evolved into Akka Persistence and is not maintained any more.

System integration

  • Open eHealth Integration Platform. A platform for developing eHealth integration solutions. Founder and lead developer during my work at ICW.
  • Apache Camel. An integration framework based on known Enterprise Integration Patterns. Contributed several integration components as well as core functionality during my work on the Open eHealth Integration Platform.





  • 1997, MS in Chemistry (Mag. rer. nat.) with distinction, Karl-Franzens Universität Graz.
  • 1996, Various courses in computer science, Karl-Franzens Universität Graz.