Python Job: Machine Learning Engineer

Job added on

Location

Hamburg - Germany

Job type

Full-Time

Python Job Details

Your Team

At Beiersdorf’s Data Science Hub we are a trusted partner to all business functions. As such we enable their digital transformation by implementing end-to-end data-driven solutions to gain advanced consumer insights and both automate and optimize business processes.
Our cross-functional team consists of experts in the fields of data engineering, data science, machine learning engineering and cloud engineering. The software solutions we implement range from demand forecasting over promo campaign optimization and consumer sentiment sensing to cognitive search engines.

Our tech stack:

  • Microsoft Azure: Data Lake Gen2, Machine Learning Workspaces, Data Factory, Container Registry, Functions
  • Databricks w/ PySpark
  • Azure DevOps and CI/CD pipelines
  • Terraform
  • Python

Your Tasks

  • Industrialization of state-of-the-art data science solutions
  • Embed data science models into ML pipelines together with Data Scientists
  • Orchestrate end-to-end data science pipelines including data and ML pipelines together with Data Engineers
  • Monitor data science models including data-drift and drift of performance metrics
  • Monitor (re-)training and inference pipelines

Your Profile

  • Master's degree in Mathematics, Physics, Computer Science or in a related quantitative field
  • Strong Python skills. Strong general software engineering skills including DevOps and CI/CD pipelines
  • Experience with training and inference pipelines for data science models
  • Experience with REST APIs and event monitoring is a plus
  • Work experience with containerization with Docker and Kubernetes is a plus
  • Fluent in written and spoken English. German is a plus
  • Ability to work in a self-organizing environment and eagerness to continuously learn

ADDITIONAL INFORMATION

You are welcome to apply without a cover letter. We look forward to receiving your application including a compelling curriculum vitae with relevant references and certificates. If you have any questions, please contact our recruiter Sarah Tönjes every Wednesday between 15h and 16h via the telephone number: +49 40 4909 4956.