(Remote/Onsite) Machine Learning (Cloud) Engineer (f/m/x)


OptioPay is working on an exciting greenfields customer facing product. We need you to build it with us and to help us go live later this year. It’s an exciting time to join the team, as you will be working on what will become a game changing experience for customers everywhere. Open Banking data plays a big role in our future, and we are very excited to work with you to ensure that customers everywhere are finally rewarded financially for the data that they generate in their day to day lives. Help us create an Open Banking revolution!

You need to be able to deploy working ML-pipelines in the cloud. We have huge sets of customer data from which we want to make helpful recommendations. Sometimes we need models to immediately return a prediction, sometimes we need batch processing of many predictions. Sometimes fitting the model might require distributed computation. Your job will be to build pipelines right for each job: from training to prediction to model evaluation and backtesting. We are a small team, while the focus of your job will be to bring models into production, you will also be able to learn a lot about building different kinds of Machine Learning algorithms.This role is ideal for engineers who already know the Dev Ops side of things and want to learn more about the ML/AI aspect of the job. Everyone in our team thinks Data Science and Machine Learning are exciting topics and we would like out next colleague to share that passion!


  • You will bring ML models into productions.
  • You will enable automated backtests on real data for a portfolio of models.
  • You will design and maintain cloud software for our data products.
  • You will create and maintain optimal architecture for our ETL pipelines.
  • You will deploy AI models as services that can be used in our platforms.
  • You will collaborate with engineering to developing solutions to scale approaches to productionize our models.


  • You have passion and great interest in building a career in Data Science / AI.
  • You have a bachelor or master's degree in Computer engineering / Computer science, Data Science, Statistics, Econometrics, or other quantitative fields.
  • You have 2+ years of full-time work experience deploying cloud solutions in production.
  • You have experience with AWS, Azure or Google Cloud.
  • You have very good programming skills; Python is preferred but other languages will work as well.
  • Knowledge of fundamentals in data science or machine learning is preferred.
  • Experience with Docker and Git is desired; Experience with Docker Compose and Kubernetes is a big plus.
  • You have strong communication skills and English proficiency, with ample experience across a wide variety of teams and disciplines in a dynamic environment.
  • You are a team player, proactive and have a strong capacity to work independently on mission critical tasks.