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Senior Research Engineer - Learning to Rank Miejsce pracy: Warszawa Technologies we use Expected Python PyTorch Tensorflow Transformers Pandas Numpy Optional Google Cloud Platform AWS Azure About the project About us: In the Learning to Rank team we develop machine learning models for search, ranking and ads. Our models serve millions of searches a day. We develop and apply state-of-the-art machine learning methods, helping Allegro grow and innovate with artificial intelligence. Beyond bringing AI to production, we are committed to advance the understanding of machine learning through open collaboration with the scientific community. About the role: As a Senior Research Engineer, you will work at the intersection of cutting-edge machine learning research and real-world products used at scale. You’ll take ownership of ML solutions end to end - from exploring complex data and selecting the right methods, to rigorous evaluation and production deployment. This role is for someone who enjoys navigating uncertainty, keeping pace with a fast-moving ML landscape, and turning research insights into tangible business impact, while also shaping ML expertise within the team and beyond. Your responsibilities End-to-end ML ownership: Design and deliver production-ready machine learning solutions for Allegro products Data exploration: Analyze and understand complex data sets, identifying relevant data sources for ML use cases Model development & evaluation: Train, evaluate, and experiment with applied ML models using reliable evaluation methods Applied ML research: Translate state-of-the-art ML research into practical improvements for real-world solutions Tooling & methodology: Select ML tools and techniques that best fit concrete business needs Production collaboration: Work closely with cross-functional teams to deploy ML solutions into production Knowledge sharing: Spread ML expertise through internal sessions, presentations, and research activities Mentorship & expertise: Support junior team members and act as a trusted ML expert within the organization Our requirements Have a masters or PhD in machine learning, mathematics, computer science, statistics or other STEM fields Have a good knowledge of deep learning techniques (neural networks, contrastive learning, semi-supervised learning) in at least one domain (information retrieval, natural language generation or understanding, etc.) Know the methodology of conducting scientific research and the use of iterative processes of conducting experiments Have experience in working with real data that deviate from the standard, well-developed collections used in research Know Python and libraries necessary to work with model development (PyTorch, Tensorflow, Transformers, Pandas, Numpy, etc.) Optional Understanding of Information Retrieval (IR) area Published research papers in ML-related topics Experience in business cooperation, deployments of ML-based solutions in commercial environments Prior experience in running large-scale computation on cloud platform (GCP, AWS or Azure) Prior experience in using LLMs for synthetic data generation/solving business problems What we offer Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work. Long term discretionary incentive plan based on Allegro.eu shares (restricted stock units). Annual bonus based on your annual performance and company results. Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms). A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you dont like Macs) and all the necessary accessories. A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers). English classes that we pay for related to the specific nature of your job. A training budget, inter-team tourism (see more here), hackathons, and an internal learning platform where you will find multiple trainings. An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal. Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy. Benefits sharing the costs of sports activities private medical care sharing the costs of foreign language classes sharing the costs of professional training & courses life insurance flexible working time integration events no dress code leisure zone extra social benefits goodtobehere means that: You will join a team you can count on - we work with top-class specialists who have knowledge- and experience-sharing in their DNA. You will love our level of autonomy in team organization, the space for continuous development, and the opportunity to try new things. You get to choose which technology solves the problem and you are responsible for what you create. You will value our Developer Experience and the full platform of tools and technologies that make creating software easier. We rely on an internal ecosystem based on self-service and widely used tools such as Kubernetes, Docker, Consul, GitHub, and GitHub Actions. Thanks to this, you can contribute to Allegro from your very first days on the job. You will be equipped with modern AI tools to automate repetitive tasks, allowing you to focus on developing new services and refining existing ones (also leveraging AI support). You will create solutions that will be used (and loved!) by your friends, family and millions of our customers. You will meet the Allegro Scale, which starts with over 1000 microservices, an open-source data bus (Hermes) with 300K rps, a Service Mesh with 1M rps, tens of petabytes of data, and production-used machine learning. You will become part of Allegro Tech - We speak at industry conferences, cooperate with tech communities, run our own blog (its been over 10 years!), record podcasts, lead guilds, and we organize our own internal conference - the Allegro Tech Meeting. We create solutions we love (and can) to talk about!