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Jobs / Machine Learning Engineer in Germany
10 days ago
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Zalando·E-commerce·10 days ago
10 days ago

Senior Applied Scientist (all genders)

Berlin, GermanyMid · 5-8 yearsMachine Learning Engineer

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Top 10% of NextRaise users matched against Machine Learning Engineer roles in Germany.

Must-have skills for this role

  • python
  • deep learning
  • reinforcement learning
  • recommender systems

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Apply faster with autofill FREEThe NextRaise extension autofills your application in one click.careers.example.com/applyAutofillingFull namePriya SharmaEmailpriya.sharma@example.comPhone+49 30 1234567LocationBerlGet the extension

What you'll do

  • Develop and deploy state-of-the-art Deep Learning and Reinforcement Learning models to power real-time content delivery algorithms across high-traffic surfaces.
  • Formulate and solve multi-objective ranking and allocation problems at scale, optimizing dynamic trade-offs between short-term conversion, long-term customer engagement, and business monetization.
  • Contribute to long-term research roadmaps for personalized content discovery and ranking, translating strategic business objectives and governance goals into concrete scientific problems.
  • Partner closely with Principal Scientists, Data/ML Engineers, and Product Managers to deliver state-of-the-art machine learning solutions to production navigating high technical uncertainty and seamlessly aligning across stakeholders.
  • Act as a mentor and technical sparring partner to scientists across the team, advocating for rigorous experimental methodologies and actively contributing to Zalando’s broader science community.

What they're looking for

  • An advanced degree (M.Sc., Ph.D.) or equivalent industry experience in Machine Learning, Applied Economics, Econometrics, Computer Science, Statistics, or a related quantitative field.
  • 6+ years of applied science experience leading end-to-end AI/ML solutions from ideation and research to large-scale production, ideally combined with a strong publication record of advancing state-of-the-art methods for real-world applications.
  • Deep hands-on expertise in Deep Learning, Recommender Systems, Reinforcement Learning/Bandits, Multi-Objective Optimization, and Causal ML coupled with extensive experience designing and evaluating complex A/B experiments.
  • Proven leadership in shaping scientific roadmaps and collaborating across Product, Science, Engineering, and senior leadership to discover business opportunities and solve complex problems with scientific solutions.
  • Strong technical proficiency in Python and Deep Learning frameworks (e.g., TensorFlow, PyTorch) for RL, and modern AI coding assistants and agents, along with hands-on experience building and scaling production recommender and ranking engines on cloud platforms (AWS).

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

THE ROLE & THE TEAM

The Content Personalization & Governance team at Zalando provides personalized content selection and ranking for Zalando’s discovery surfaces. A key part of our mission is to drive Zalando's evolution into an inspiring ecosystem that seamlessly integrates shopping, storytelling, and style inspiration through the Home Feed -  the platform's first touchpoint with millions of active fashion customers. The team sits at the critical intersection of algorithmic relevancy and business value. Using state-of-the-art deep learning and reinforcement learning models, we are building intelligent content discovery systems that maximize immediate monetization while driving long-term customer loyalty.

As a Senior Applied Scientist, you will play a central role in building and scaling the next generation of these discovery systems across the platform. In this position, you will join a high-impact, multi-disciplinary science and engineering team and lead high-impact research and productionization initiatives, combining recommender systems, ranking algorithms, and economic trade-off modeling to shape the future of personalized discovery at scale.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING) 

  • Develop and deploy state-of-the-art Deep Learning and Reinforcement Learning models to power real-time content delivery algorithms across high-traffic surfaces.

  • Formulate and solve multi-objective ranking and allocation problems at scale, optimizing dynamic trade-offs between short-term conversion, long-term customer engagement, and business monetization.

  • Contribute to long-term research roadmaps for personalized content discovery and ranking, translating strategic business objectives and governance goals into concrete scientific problems.

  • Partner closely with Principal Scientists, Data/ML Engineers, and Product Managers to deliver state-of-the-art machine learning solutions to production navigating high technical uncertainty and seamlessly aligning across stakeholders.

  • Act as a mentor and technical sparring partner to scientists across the team, advocating for rigorous experimental methodologies and actively contributing to Zalando’s broader science community.

WE’D LOVE TO MEET YOU IF YOU HAVE…

  • An advanced degree (M.Sc., Ph.D.) or equivalent industry experience in Machine Learning, Applied Economics, Econometrics, Computer Science, Statistics, or a related quantitative field.

  • 6+ years of applied science experience leading end-to-end AI/ML solutions from ideation and research to large-scale production, ideally combined with a strong publication record of advancing state-of-the-art methods for real-world applications. 

  • Deep hands-on expertise in Deep Learning, Recommender Systems, Reinforcement Learning/Bandits, Multi-Objective Optimization, and Causal ML coupled with extensive experience designing and evaluating complex A/B experiments.

  • Proven leadership in shaping scientific roadmaps and collaborating across Product, Science, Engineering, and senior leadership to discover business opportunities and solve complex problems with scientific solutions.

  • Strong technical proficiency in Python and Deep Learning frameworks (e.g., TensorFlow, PyTorch) for RL, and modern AI coding assistants and agents, along with hands-on experience building and scaling production recommender and ranking engines on cloud platforms (AWS).

OUR OFFER

Zalando provides a range of benefits, here’s an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.

  • Employee shares program

  • 40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners

  • 2 paid volunteering days a year

  • 27 days of vacation a year to start

  • Relocation assistance available (subject to prior agreement)

  • Family services, including counseling and support

  • Health and wellbeing options (including Gympass)

  • Mental health support and coaching available

  • Drive your development through our training platform and biannual peer-to-peer review

  • Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us
     

INCLUSIVE BY DESIGN

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. ​

  • 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. 

  • do.BETTER - our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy
    Our employee resource groups: https://corporate.zalando.com/en/our-impact/our-employee-resource-groups

  • Opportunity to work from abroad for 30 (working) days per calendar year

E-commerce

Company

ZalandoE-commerce
Berlin, Germany

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Zalando's careers site·first seen 10 Sept 2026·last verified 10 Sept 2026·How we source jobs

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