Principal Applied Scientist 100%

The Role and the Team

The DAGT team builds state-of-the-art machine learning systems, including recommendation systems, GenAI/LLMs, and neural search, to tackle high-impact problems across the customer journey. Our aim is to create experiences that are not only exciting and engaging but also deeply relevant.

In this role, you will play a key part in addressing challenging fashion problems through innovative approaches that influence how over 53 million customers discover, choose, and purchase fashion. You will contribute to our scientific roadmap, applying your expertise to deliver impactful projects in collaboration with diverse teams. Working closely with science leaders, you will guide a talented team of scientists and engineers in developing cutting-edge machine learning products to enhance customer experiences.

Responsibilities

• Utilize your extensive scientific experience to research, deploy, and architect machine learning and deep learning solutions that enhance the customer journey.
• Collaborate with various teams to create a science stack that aligns with product strategy and drives architectural and design principles.
• Develop long-term scientific roadmaps to tackle complex fashion challenges, ensuring our continued position at the forefront of innovation.
• Contribute to scientific developments through peer reviews and publications in top-tier journals and conferences.
• Act as a mentor to junior and senior scientists, promoting collaboration and knowledge sharing within the science community.
• Build strong partnerships with applied science leaders, product managers, and business stakeholders to deliver advanced machine learning solutions and identify growth opportunities.

Qualifications

• PhD in computer vision, deep learning, search & recommendation, or related fields (or equivalent experience), with 6+ years of industry experience.
• Experience in developing long-term research roadmaps and applying scientific methods to address research challenges.
• A strong capability to collaborate with product, science, and engineering managers to solve business problems through scientific approaches.
• Demonstrated experience in addressing large-scale real-world issues using machine learning across the entire product cycle, including problem analysis, data processing, literature review, production deployment, monitoring, and maintenance.
• Strong publication record at top-tier venues such as SIGIR, KDD, WWW, ICLR, NeurIPS, ICML, JMLR, etc.
• Extensive hands-on experience in deep learning with proficiency in Python and frameworks like PyTorch or TensorFlow.

Perks

• Culture of trust, empowerment, and constructive feedback, with a commitment to open source.
• Exciting meetups, game nights, 70+ internal technical and fun guilds, and opportunities for knowledge sharing through tech talks and product demos.
• Competitive salary, employee shares program, 40% Zalando shopping discount, and other partner discounts.
• Flexible working times, additional holidays, and volunteering time off, alongside free beverages, fruits, and a variety of sports and health offerings.
• Extensive onboarding, mentoring, and personal development opportunities within an international team of experts.
• Relocation assistance and family services available in select locations.

Our Commitment to Inclusion

At Zalando, we envision a leading pan-European ecosystem for fashion and lifestyle e-commerce—one that is inclusive by design. We assess candidates solely based on qualifications, merit, and business needs, welcoming applications from diverse backgrounds.

We aim to provide an exceptional experience throughout the hiring process, and we encourage communication regarding any accommodations needed for support.

Discover more about our diversity and inclusion strategy at here.

Benefits Overview

• Employee shares program.
• Discounts on Zalando products and external partners.
• Paid volunteering days.
• Hybrid working model with flexible remote options.
• Generous vacation policy for full-time employees.
• Health and wellbeing options, including mental health support.
• Professional development through training platforms and peer reviews.