Machine Learning Engineer

About AI Incubator

We are a small team in a big company, mainly adopting agile methodology. We provide Data Science solutions for internal customers inside Deutsche Telekom and our skills and solutions are continually in high demand. Therefore, we want to increase size of our team with additional technical people that know how to process and analyze data so we can serve and satisfy needs of even more customers.

We are looking for somebody who can work independently, create working solutions quickly, creatively come up with new ideas, but also knows how to use and where to look for existing solutions. Our project members are also situated in Germany, Slovakia or Romania so videoconferencing is the daily standard.

Which challenges are expecting you:

  • you will support the AI project teams, especially the forecasting delivery unit, to implement and improve the data processing & machine learning pipelines across projects
  • you will be the backbone for our Data Scientists, and work closely with team members and internal customers in Deutsche Telekom Group across Europe to optimize our data solutions and infrastructures
  •  you will evolve, harmonize, and refactor the existing solutions across projects
  • you will validate and implement business changes in the code repository and ensure its standardization
  • you will have the opportunity to work with a variety of tools and technologies like Python, Scikit-learn, Keras, Spacy, Docker, Kubernetes, Flask, SAP or Tesseract and BI dashboarding tools like MicroStrategy, SAC, Tableau, … knowledge of these is helpful
  • you will develop and maintain applications in our server / cloud environment
  • you will assist data scientists with productization of prototype applications – e.g., logging, monitoring, testing
  • you will write documentation and guidelines
  • you will automate processes for ETL
  • you will identify, design, and implement internal process improvements: e.g., automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
  • you will participate in designing data architecture for various innovative prototypes and applications
  • you will create data tools for analytics and data scientist team members

Your skills:

  • you have working experience in IT – e.g., software development, automation, devops, data science – with good understanding of time series forecasting and its scalability
  • you are good at coding in Python
  • you prefer Linux to Windows
  • you have experience working on a fully automated CI / CD pipeline
  • you have SQL knowledge and experience working with relational databases
  • you follow current trends in IT
  • IT area sounds good to you, but business process management is something that seems to be interesting too (Financial Controlling, Procurement, Human Resources)
  • you will cooperate with business (meetings and calls with internal customers regarding their needs), so the ability to explain technical stuff to business colleagues is a crucial part of this job
  • you are a team player, open for international environment and can travel occasionally within Europe. Mostly to Germany
  • we communicate in English daily, but also Czech, Slovak and/or German are useful
  • you are not afraid to ask questions when something is not clear or point out when something seems inefficient to you
  • you are an analytical thinker, have an affinity for structure, grasp things fast and work systematically
  • you can develop working solutions quickly and you get things done
  • you are aware of and willing to apply Agile methodology (Scrum, XP, Kanban etc.)

Nice to have skills

  • you know how to deploy applications in Flask or similar framework
  • you know how to develop and maintain APIs
  • you’ve worked with remote servers and clouds before
  • you’ve worked with SAP or are prepared to learn it
  • you’ve worked with unstructured datasets
  • you’ve worked with Docker, Kubernetes, AWS, Openshift or similar tools
  • you have experience with Big Data technologies

 

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