Together with our partner, a prominent Online Fashion & Beauty Retailer in Europe, we’re looking for an experienced Applied Scientist to join a Discovery Team!
The Discovery team assists customers in their fashion discovery journey and helps them find what they are looking for. We are developing the next generation of our discovery systems, utilizing state-of-the-art recommender systems, natural language processing (NLP) methods, particularly transformer-based deep neural networks and large language models (LLMs).As a Senior Applied Scientist you will play a key role in addressing challenging fashion problems using cutting-edge approaches. You will help drive our scientific roadmap, applying your scientific capabilities to deliver department-wide and cross-department projects in collaboration with multiple teams. Working closely with Zalando science leaders, you will guide a team of exceptional scientists and engineers to develop models and cutting-edge machine learning products that enhance the experience of over 51 million customers.
Utilize your extensive scientific experience in researching, deploying, and architecting machine learning and deep learning solutions in IR to enhance the inspiration journey of millions of our customers. Collaborate with multiple teams to create a cutting-edge science stack that aligns with the product strategy and drive architectural and design principles.
Develop long-term scientific roadmaps to address complex fashion challenges using state-of-the-art solutions, ensuring we stay at the forefront of IR innovation. Contribute to our scientific endeavors through internal peer reviews and external publications in top-tier journals and conferences.
Act as a mentor to junior and senior scientists, foster collaboration with other teams, and actively share knowledge and expertise within Zalando’s science community.
Forge close partnerships with applied science leaders, product managers, and other business stakeholders to deliver state-of-the-art machine learning solutions to our customers and uncover new opportunities for growth.
PhD in IR, search & recommendation, information & knowledge management, or related fields (or equivalent experience), accompanied by 6+ years of industry experience in modern IR systems, especially neural IR. Comprehensive understanding of the key components of an IR system, including query processing, indexing, evaluation, etc.
Experience in developing long-term research roadmaps and applying scientific methods to tackle research problems. A strong inclination to collaborate with product, science, and engineering managers and solve business problems through scientific solutions.
Extensive track record of addressing large-scale real-world problems using machine learning throughout the entire product cycle, encompassing problem analysis, data processing, literature review, production deployment, monitoring, and maintenance.
Publication records 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. Familiarity with LLMs. Proficiency in full-text search engines such as Elasticsearch, OpenSearch, Apache Lucene is also desired.
Knowledge of classical IR models is a plus (boolean, vector, and probabilistic).