Senior Machine Learning Engineer - Transport Network and Planning (all genders)

<h2>THE ROLE AND THE TEAM</h2><p><span>Zalando fulfills more than a hundred million customer orders every year and volumes are increasing. Transport within Zalando builds and operates systems that are at the core of Zalando’s platform strategy and ensure timely, efficient, and correct delivery of every one of our customers’ 185+ million orders and shipments every year.</span><br/> </p><p><span>Enabling the fulfillment of orders is a complex process, involving the choice of physical locations of our warehouses to our Hubs: This is the backbone of logistics where movements occur. Efficient network routing and capacity planning optimise utilise (e.g., trucks, linehauls) and reduce transit times, directly impacting service levels and cost per unit transported. Notably, the middle mile is closely steered by the requirements of the last mile — meaning last mile delivery demands often dictate middle mile scheduling and consolidation decisions. This makes integrated planning between the two critical for transport network efficiency.</span><br/> </p><p><span>The last mile is often the most complex and expensive segment. Smart planning here, including optimal route design and delivery slot management, is crucial for meeting customer expectations on speed and reliability while keeping delivery costs manageable. Since the last mile drives the timing and structuring of middle-mile operations, its importance in the overall transport domain is amplified.</span><br/> </p><p><span>As a <b>Senior Machine Learning Engineer</b>, you will be essential in defining and managing the next generation of our engineering infrastructure (e.g. data ETL pipelines, train/inference deep learning model pipelines, and many more). You will be part of a skilled team of data engineers and ML engineers address complex transport network and planning challenges, improve the optimisation of the network, and supporting many highly important strategic and data-driven use-cases, such as network design simulation and optimisation, dynamic slot and carrier recommendation, and simulation for disruption management. This role offers a unique chance to be at the forefront of Zalando's technological advancement, enhancing your engineering expertise in a high-impact and dynamic environment.<br/><br/>You can read more about our department here: </span><br/><span>https://jobs.zalando.com/en/blog/logistics-tech-capabilities-at-zalando</span></p><p></p><h2>INCLUSIVE BY DESIGN</h2><p><span>At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit. </span></p><p></p><p><span>We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process. </span></p><p><span>do.BETTER - our diversity &amp; inclusion strategy: </span><a href="https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy" rel="noopener noreferrer" target="_blank"><u><span>https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy </span></u></a></p><p><span>Our employee resource groups: </span><a href="https://corporate.zalando.com/en/our-impact/our-employee-resource-groups" rel="noopener noreferrer" target="_blank"><u><span>https://corporate.zalando.com/en/our-impact/our-employee-resource-groups </span></u></a><br/> </p><h2>WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)</h2><ul><li><p><span>Work closely with software engineers and data engineers to deploy Machine Learning models to a production environment</span></p></li><li><p><span>Design, build, and maintain Machine Learning models and its data pipelines</span></p></li><li><p><span>Utilise a cloud-based tech stack including SageMaker, Databricks, and AirFlow</span></p></li><li><p><span>Implement best practices in software engineering, including code quality and testing for the Python codebases</span></p></li><li><p><span>Ensure system stability and improve monitoring and resilience</span></p></li><li><p><span>Mentor others, drive innovation, and foster a positive and inclusive work environment</span></p></li><li><p><span>Be part of Zalando’s engineering community and the advocate team’s processes</span></p></li></ul><h2></h2><h2>WE’D LOVE TO MEET YOU IF</h2><ul><li><p><span>You have at least <b>6 years</b> of industry <b>experience in designing, developing and operating data-intensive Machine Learning systems</b>.</span></p></li><li><p><span>You have experience in developing and implementing statistical or predictive models</span></p></li><li><p><span>Experience working together with data engineers, and familiar with traditional processes from ideation to pro