Job description

Would you like to be part of the most international company in the world? A company operating in more than 220 countries worldwide, and has been pioneering cross-border express shipping since 1969. Would you like to be part of a business that connects people across the globe? And the more we connect, the better life on Earth becomes. Do you want to make a difference? If you have answered Yes! to the above, join our Insanely Customer-Centric team now! For more information on DHL Express, please visit

DHL Express Global Head Office has an opening for Machine Learning Engineer (Senior System Specialist) . The Machine Learning (ML) Engineer is responsible for taking proven data science models and helping to scale them to production-level models that can handle terabytes of real-time data with the right analytics design and technology; ensuring stability and evolution of the models in production; contributes to technical development of advanced analytics platforms.


Project Team Management

  • Collaborate with other project team members and ensure that analytics best practices are implemented.

IT Systems Development, Configuration & Testing

  • Accountable on technical input into the design, development, implementation of ML- solutions (API, batch scoring).
  • Own the configuration and Implementation of ML-pipeline using the agreed technologies components (e.g. openshift).
  • Accountable (own) the completeness and accuracy of the MLOps Requirements.
  • Accountable for quality assurance and testing of ML-solutions within the scope of the project.
  • Meet project milestones.
  • Train, retrain and evolve ML-solutions, when necessary.

Technology, Touchpoint, People and Processes

  • Provide input on applicability of new technologies to the data analytics development process.
  • Build an effective relationship with internal and external stakeholders.

Application & Deployment Coverage Scope

  • Primary (Beta) deployment focus for IT Services will be for TIER 1 countries.
  • Able to perform multiple deployments concurrently.


  • Minimum 4 years of experience in data-intensive product development.
  • Minimum 4 years of experience in DevOps.
  • Minimum 2 years of experience in Machine Learning Ops.
  • Professional Certification in Agile (preferable).
  • Solid experience with data structures, data modeling, algorithms and software architecture.
  • Experience using machine learning pipeline for production or commercial products.
  • Software development experience through hands on coding in a general purpose programming language.
  • Proficient in writing complicated SQL, Python/Flask, Java/SpringBoots code.
  • Experience working with Airflow, MlFlow, similar open source.
  • Experience working with containerization Openshift, Docker.
  • Background in machine learning frameworks such as TensorFlow or Keras.
  • Machine learning domain knowledge and understanding of various model families, including regression, decision trees, and neural net.
  • Experience working Agile and DevOps; familiar with DataOps.
  • Understanding of cloud storage, hosting, and compute environments.
  • Must be able to work collaboratively with cross-functional and cross-geographical teams.
  • Good oral and written English: ready to present to technical audience.
  • Analytical: Synthesize complex or diverse information; Able to source and prepare data; Design data flows and Data models; Challenge and re-validate conclusions.
  • Design: Apply design principles; Demonstrate attention to details.
  • Problem Solving: Identify and resolve problems in a timely manner; Foresee and communicate potential issues; Develop alternative solutions; Work well in group problem solving situations.
  • Business Acumen: Understand business implications of data for decisions

Advanced degree or equivalent experience in: Computer Science, Engineering, Information Systems

Do you see a personal challenge in these versatile and responsible tasks? Apply now - we look forward to receiving your application!


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