Bridging the gap between academic research and at-scale development

Currently, there is a significant gap between specialized academic research on deep learning and the at-scale application of these concepts to solving real problems. At Merantix, our goal is to aggregate concepts and technical research and use them to create scalable and relevant deep-learning solutions. In order to reach these goals, our team is closely connected to researchers at major academic institutions, with whom we collaborate on various topics. We recognize the importance of bringing groundbreaking research on deep learning to life and we strive to realize with our constantly evolving products and solutions.

Applied Research Topics

Reinforcement Learning

How software agents ought to take actions in an environment so as to maximize a suitable notion of cumulative reward.

Bayesian Deep Learning

Provides a deep learning framework which can also model uncertainty. BDL can achieve state-of-the-art results, while also understanding uncertainty.

Introspective Analysis of Neural Networks

Debugging neural networks can be challenging, even for experts. With millions of parameters involved, even one small change can cause errors. At Merantix, we develop methods to visualize neural nets to make this process smoother.

Continuous Learning

Learning continuously and adaptively about the external world and enabling the autonomous, incremental development of ever more complex skills and knowledge.

Neural Network Compression

Compression of deep neural networks for memory-efficient, compact feature representations becomes a critical problem when these networks are deployed on resource-limited platforms.

Label Noise

Well-annotated datasets can be prohibitively expensive and time-consuming to collect. Our research explores the usage of larger albeit noisier datasets that can be more easily obtained.

Modularization of ML Pipelines

Our team is experimenting with the modularization of machine-learning pipelines in order to achieve maximum efficiency throughout complex processes.

Improving Experimentation Cycles

Experimentation is a crucial part of our work at Merantix. We are constantly improving experimentation cycles to be able to run more and more experiments.

Initiator and Member of

Horizon 2020

Research Member of SECREDAS Project

VDA (German Association of the Automotive Industry)

Member of the VDA Lead Initiative for Safeguarding Autonomous Vehicles

Merantix was selected by the European Commission to take part in a Horizon 2020 project on Cyber Security for Cross Domain Reliable Dependable Automated Systems (SECREDAS). Within SECREDAS Meratnix is a core contributor developing robust and secure image segmentation algorithms, that function reliably in corner-case situations as well as when faced with real-world adversarial attacks. Horizon 2020 is the financial instrument implementing the Innovation Union, a Europe 2020 flagship initiative aimed at securing Europe's global competitiveness. Seen as a means to drive economic growth and create jobs, Horizon 2020 has the political backing of Europe’s leaders and the Members of the European Parliament. The goal is to ensure Europe produces world-class science, removes barriers to innovation and makes it easier for the public and private sectors to work together in delivering innovation.

Merantix is a member of the VDA Lead Initiative on safeguarding autonomous vehicles, which aims to build both technology and industry standards to enable the scaled development and deployment of autonomous systems. The German federal government of has set the goal of ensuring Germany’s pioneering role in self-driving technology. Working closely with all major German OEMs and Tier 1 suppliers, Merantix is contributing to make detection and segmentation algorithms robust. Furthermore we are collaborating to develop semantics and standards for safe autonomous vehicles as well as concepts for scalable testing environments.

PRESENT AT

Recently in our paper discussion sessions

Careers at Merantix

Engaging Topics

Merantix encourages you to pursue your curiosity and passion for several diverse topics. We are dedicated to addressing machine-learning problems that are challenging and foundational to an entire industry. We believe that diversity across topics is essential to attracting and retaining the greatest talent and to promoting creativity, continuous improvement, and functional learning.

Professional Development

Merantix is proactive in making major contributions to the open-source community. We encourage all of our employees to regularly attend professional conferences. Merantix is a regular guest at notable academic conferences on machine learning such as NIPS, ICCV, ICLR and ECCV. At the ECCV event this September, we will host an Italian Night with great food where you will be able to get in touch with all of us.

Work-Life Balance

Merantix offers a dynamic and flexible work environment. Some of us come in during “regular” business hours, and some prefer to start later or earlier. Our employees have the freedom to work when it best suits them. We are a fully trust-based organization that does not track vacation time. We believe in ownership of work, personal responsibility, and the motivation of our people, which has proven to be a successful approach to leadership

 

Collaborative Culture

Merantix is a family of diverse people from all over the world that came to Berlin to work on machine learning. We truly care about the individual well-being of our employees and support all of our new employees who are joining us in Berlin with whatever they may need. We have regular offsites and encourage everyone to organize common activities; just join the “all-sports” slack channel and stay up-to-date on bouldering, swimming, running, and much more.

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