Why should you work at Allegro?

• Being a part of Machine Learning Research team, you will be responsible for finding solutions to research problems that we encounter at Allegro
• While working on a new problem, you will explore it in depth and conduct literature review, looking for the most promising techniques for a given problem
• You will be responsible for the preparation of the production-grade machine learning models, supporting the development team for a correctly functioning production model and meeting desired latency requirements
• You will support other teams in the implementation of tasks requiring the use of ML models. Your support will be needed both at the technical (e.g., what architecture will be appropriate for the domain) and best-practices level (e.g., building data sets, modeling, metrics, implementation of the ML-based solutions to the production) 
• To apply state-of-the-art solutions, you will stay up to date with the scientific progress. You will deepen your knowledge by reading the latest papers in your domain, sharing the knowledge with other team members of the research teams operating in Allegro. You will participate in scientific conferences, visiting places where the latest discoveries are presented
• You will have the possibility to share the results of your research in the scientific community, and by taking part in the scientific conferences (oral presentations, poster sessions). You will develop your scientific career, as well as Allegro's presence in the science community
• In your daily work you will expand your knowledge by cooperating with people who have hands-on experience in implementation of the ML models at scale unprecedented anywhere else in Poland

What we can offer:

• Startup work culture and a stability of the mature organization
• Modern office and work tools
• Informal atmosphere in a professional team
• A large package of non-wage benefits in the cafeteria system 
• English classes designed with the engineers in mind

We are looking for candidates who:

• Have a master's or PhD in machine learning, mathematics, computer science, statistics or related fields
• Have a good knowledge of machine learning techniques (neural networks, random forests, Bayesian models) in at least one domain (information retrieval, natural language processing and understanding, time series, etc.)
• Know the methodology of conducting scientific research and the use of iterative process of conducting experiments
• Have experience in working with real data that deviate from the standard, well-developed collections used in research
• Use statistical methods
• Know Python and libraries necessary to work with model development (XGBoost, LightGBM, Tensorflow, PyTorch, Pandas, Numpy, etc.)