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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.
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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