Machine Learning Engineer

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 workingatdhl.com.

DHL Express Global Head Office has an opening for Machine Learning Engineer . 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.

YOUR TASKS

Project Team Management

• Collaborate with other project team members and ensures 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.
  

WHAT WE NEED FROM YOU

• 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.
• 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
• Professional Certification in Agile (preferable).
• 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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