An ambitious and fast-growing startup in the field of Information Technologies (FINAL CUSTOMER) is looking to hire a Machine Learning Engineer for their Headquarters in Berlin.

REQUIREMENTS (Not all of it, but most of it):

– Bachelor´s degree in quantitative discipline, either Computer Svience, Statistics, Physics, Applied Mathematics), Master´s degree preferred.
– Hands on experience with statistical analysis, visualization and data mining tools such as R, Hadoop, Spark, S3, EMR or similar tools.
– Mobile development experience (Swift or JAVA/Kotlin) and backend development: ideally both.
– SQL and NoSQL database systems practical experience.
– Experience in statistical modelling, algorithm development, and data mining of massive datasets and events.
– Experience in machine learning, ideally in pattern recognition in time series data
– DevOps experience (AWS) is a plus.
– Ability to work and communicate in a fast-paced international environment.
– Results oriented personality willing and motivated to work in an agile startup where things change fast.
– Very high level in English (C1/C2), German is an asset but no obligatory.
–  Motivation to be flexible in an agile start-up – things change fast!


-Attractive salary.
– Work in ambitious startup with multinational clients.
– Believe in authenticity and mutual support
– Inspiring, intercultural and fun team
– Remote work possible.
– Location in startup city #1 in Germany: Berlin.

 Sounds like you or would like to get more information?

APPLY NOW by filling in the form below or by sending us your CV directly with a subject “MACHINE LEARNING ENGINEER / PYTHON EXPERT – BERLIN” at

and Let´s Build The Future Together!

To apply for this job email your details to


This site uses cookies: Find out more

Receive this free in your email

I would like to receive more information about Fut-Ure and its services. I hereby consent to receive electronic messages and other communications from Fut-Ure.


We have received your submission, check your inbox to download your FREE guide
There was an error in submitting your form.


    Accept data privacy policy