Opis oferty:

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.

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.

In your daily work you will handle the following tasks:

• 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

Wymagania:

• Have a master's 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.)

Dodatki i korzyści:

• Flexible working hours in the hybrid model (4/1) - working hours start between 7:00 a.m. and 10:00 a.m.
• 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 and excellent work tools
• A wide selection of fringe benefits in a cafeteria plan
• English classes related to the specific nature of your job
• A training budget, inter-team tourism, hackathons, and an internal learning platform
• An additional day off for volunteering
• Social events for Allegro people