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Apply as Machine Learning Engineer (f/m)

We don't do big data - we do HUGE data.

Machine Learning Engineer (f/m)

We don't do big data - we do HUGE data.

We're looking for a Machine Learning Engineer (f/m) to become part of our outstanding development team in Munich. You are responsible to develop new features that help us to improve our data analysis and prediction generation. If you love to continuously improve and deliver high quality software - then maiot is the place to be for you!

About maiot

maiot is a young startup in the field of big data analytics based in Munich. Our vision is to predict breakdowns of commercial vehicles (trucks, buses, etc.) to cut costs and to facilitate the life of the fleet managers by using machine learning techniques. We are quickly growing and constantly looking for motivated team members to join. What unites us is our passion to work on cutting-edge technology, the willingness to go 'one step further' and the great fun we enjoy together at work and in our free time.

Why work with us?

  • Work in an agile environment with full personal responsibility for your projects
  • Develop your soft- and hard skills on-the-job and in diverse workshops
  • Opportunity to become one of our lead developers
  • Benefit from our strong network to the Munich startup world, the UnternehmerTUM, and the CDTM
  • Regular team events, including sailing and hiking trips, BBQs, Octoberfest, and evenings in the beer garden

You will work on

  • Explore real-world datasets from the trucking Industry
  • Conceptualize data pipelines to transmit live data from our trucks
  • Train, evaluate, and deploy state-of-the-art ML / DL models
  • Visualize your data analysis results

Your Profile

  • You either have at least a bachelor degree in a field like mathematics, statistics, computer science, mechanical/electrical engineering or equivalent practical experience.
  • You proved that Python is your native language
  • You are experienced in training, testing and deploying ML/DL models such as CNNs/RNNs/LSTMs
  • You already worked with frameworks such as Keras, Tensorflow or Pytorch
  • You are experienced with big data technologies like Apache Spark, Beam, Docker, Kubernetes and you are familiar with data processing pipeline tools such as Kafka/Google PubSub
  • You enjoy working independently, like to deal with new challenges and have a positive hands-on attitude
  • Knowledge in the English language is necessary, German proficiency is a plus
  • You participated in Kaggle challenges or collected hundreds of stars on GitHub? We are excited to hear your story!

Join our Team

Send us an email and apply!


Your application should at least contain your full curriculum vitae. Relevant certificates or documents can of course be included. Put all of them in an email and send it to: careers@maiot.io

Our hiring process

Once you apply our team will carefully review your CV and application in an initial screening. After that your journey with us will follow this outline:

The phone interview (ca. 15 minutes)
In a short phone call we will give you the gist of the position, give you the chance to ask initial questions and allow us to get a feeling for you as a person. We strongly believe in our culture and want to get to know you. What movitates you, where do you come from - WHO are you?
The challenge (depends on the position, usually 2-5h)
We don't like whiteboard interviews and weekend-filling coding challenges. You're a pro, and we want to give you a platform to show that - in an environment you like. Your editor, your machine, your setup. All our challenges will be based either directly on the role you applied for or be as similar as it can get, because you deserve to get a glimpse at what you'll be doing, too.
The onsite interview (ca. 1.5 - 2 hours)
This will be the main interview, and most importantly your chance to get to know us. We want to know your superpowers, your skills that make you you. And since you spent time ont the challenge we gave you we'd like to know how it went, how did you solve it, can we improve it?
The grande finale (ca 30 - 60 min)
Every journey has its finale. You'll meet your future team and get the chance to talk shop with them.