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DHL Express Global Head Office has an opening for Machine Learning Engineer (Senior Systems 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
- Collaborates 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).
- Owns the configuration and Implementation of ML-pipeline using the agreed technologies components (e.g. openshift).
- Accountable (owns) the completeness and accuracy of the MLOps Requirements.
- Accountable for quality assurance and testing of ML-solutions within the scope of the project.
- Meets project milestones.
- Trains, retrains and evolves ML-solutions, when necessary.
Technology, Touchpoint, People and Processes
- Provides input on applicability of new technologies to the data analytics development process
- Builds 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.
Advanced degree or equivalent experience in: Computer Science, Engineering, Information Systems
- 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
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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