JOIN OUR TEAM IN BONN OR BERLIN FOR A FULL-TIME POSITION, STARTING AS SOON AS POSSIBLE
MACHINE LEARNING OPERATIONS ENGINEER (M/F/X)
DO YOU WANT TO MAKE A DIFFERENCE?
WE OFFER EXCELLENT OPPORTUNITIES FOR QUICK LEARNERS.
DHL Group team is the leading mail and logistics service provider for the world. As one of the planet’s largest employers operating in over 220 countries and territories, we see the world differently. Join our team and discover how an international network that’s focused on service, quality and sustainability, is able to connect people and improve lives through the power of global trade. And not just for our customers, but for every member of our team, too.
DHL Data & AI is a service line in DHL Group, focusing on leveraging data to create business value. It consists of a dynamic, innovative, and globally diverse team with approximately 120 talented professionals, including Data Engineers, Cloud Engineers, DevOps Engineers, Data Scientists and Architects. With presences in Singapore and Italy, Bonn serves as DHL Data & AI headquarter. The team’s purpose is to unleash the power of data science, drive x-Business Unit AI solutions, foster a data-driven culture, and accelerate digitalization within DHL Group. As part of its work, the team is responsible for creating and maintaining robust data platforms and data pipelines to ensure accurate and efficient data processing and analysis. The team embraces diversity with over 20 nationalities represented and a 30% female workforce, fostering collaboration and the pursuit of excellence.
Your tasks.
DHL introduced a modern Kubernetes based data science platform, making use of the open source Kubeflow solution. Our environment gives you the chance to work with state-of-the-art open source components combined with carefully chosen vendor backed solutions.
As MLOps Engineer, you'll play a crucial role in professionally building, deploying, and running state-of-the-art machine learning use cases with cutting-edge technology. You'll help data scientists transition their activities from informal exploratory data analytics (e.g., Jupyter notebooks) to production-ready services and structured ML pipelines.
This role involves hands-on development, deeply integrated with DevOps principles, across the full lifecycle of our ML applications where you will:
•\tDevelop and maintain robust ML pipelines using Kubeflow Pipelines, using Python for component reusability, modularity, and efficient data handling, while ensuring robust version control and reproducibility.
•\tWrite production-grade Python based machine learning applications, ensuring robustness, scalability, and optimized deployment in containers.
•\tDevelop and integrate robust CI/CD pipelines for ML applications, automating the build, test, and deployment processes directly onto Kubernetes clusters
•\tUse Kubernetes base components and concepts to deploy containerized ML applications.
•\tAssess ML application resources configuration (e.g CPU, GPU and memory requirements) in order to provide optimal usage of our resources.
•\tUtilize Kubernetes' native monitoring capabilities (e.g., Prometheus, Grafana) and implement custom metrics to track ML model performance, resource consumption, and detect issues like model drift
Your profile.
•\tYou bring:
o\tBSc / MSc in Data Science, (Business) Analytics, Computer Science, Maths, Statistics , Physics, (Industrial) Engineering or related natural sciences / technical degree
o\t2-3 years of work experience in MLOps or ML engineering
o\tProficiency in writing clean, modular, production-grade Python code and applying software engineering principles.
o\tExperience with common Python ML/data science libraries (e.g., scikit-learn, pandas, polars, NumPy, TensorFlow/PyTorch fundamentals).
o\tRoutine experience with common Python tooling like pip, virtual environments etc.
o\tHands-on experience with Kubernetes application development
o\tFamiliarity with containerization principles (e.g. Docker) for building and optimizing images.
o\tExperience designing and implementing CI/CD pipelines for software and/or ML applications.
o\tBasic understanding of monitoring concepts and familiarity with Prometheus and Grafana.
o\tProficiency with Git and collaborative development workflows.
o\tFluency in English
•\tYou want to:
o\tDeep dive into GitOps principles and hands-on experience with ArgoCD for Kubernetes deployments.
o\tGain experience with defining infrastructure and configurations as code (IaC).
o\tWork on a variety of state-of-the-art ML and AI solutions for a global company with many different fields of application
•\tBonus points for practical experience with any of:
o\tCollaboration with Data Scientists
o\tAny open source or proprietary ML lifecycle management tooling and platforms like AWS Sagemaker, Azure ML, Google Vertex AI, MLFlow, …
o\tKnowledge about software security, cloud infrastructure, databases, data engineering or other related fields
o\tAdditional programming languages
Your benefits.
At DHL Data & AI, we offer an array of benefits designed to support your professional growth and personal well-being. Here's what you can expect when you join our team:
•\tComprehensive training programs, workshops, and e-learning resources to prioritize your growth and development.
•\tA flexible work arrangement that blends remote work and office presence, promoting work-life balance and adaptability.
•\tA competitive salary package, inclusive of various benefits, to ensure employee well-being and satisfaction.
•\tDiverse commuting options, including a job ticket for public transportation, parking space for a monthly fee, or bicycle leasing, to suit your preference.
•\tAccess to DHL Group's daycare facilities for working parents.
•\tA dynamic, cooperative, and international environment that encourages new insights.
\n\nYour contact.
For recruiting/ process related questions please send your questions in viaanalytics.recruiting@dhl.com
Interested in this responsible position with its varied tasks? Please click on “Apply Here” and send usyour complete application, including your CV, academic and professional references, your desiredsalary and your earliest possible starting date.
You can find us here:LinkedIn DHL Data & AI
We are looking forward to your application.
CONNECTING PEOPLE. IMPROVING LIVES.