Research Engineer - Machine Learning (Reinforcement Learning)
- Full-time
Job Description
In the recommendation team, we are working on personalization of our platform. Our aim is to generate relevant recommendations to our users in the most appropriate manner in terms of time, context and products. Currently, we are looking for people to start Reinforcement Learning recommendation solutions. You will be doing a literature review and you will be working on the first implementation which will be tested on the large-scale e-commerce platform.
Why should you work at Allegro?
Being a part of the Machine Learning Research team, you will be responsible for developing solutions in automated decision making (RL) for recommendation problems that we encounter at Allegro
While working on a new problem, you will explore it in depth and conduct a 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
To apply state-of-the-art solutions, you will stay up to date with scientific progress. You will deepen your knowledge by reading the latest papers in your domain and sharing the knowledge with other team members of the research teams operating in Allegro
You will have the possibility to share the results of your research in the scientific community by taking part in the conferences (oral presentations, poster sessions). You will develop your career, as well as Allegro's presence in the world of science
In your daily work, you will expand your knowledge by cooperating with people who have hands-on experience in the implementation of the ML models at a scale unprecedented anywhere else in Poland
What we can offer:
Startup work culture and 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
20% of your work time for individual ML research
Training budget and a broad selection of internal training courses
Participation in top-tier ML/AI international conferences (NeurIPS, ICLR, ICML, ACL, CVPR, ICCV, etc.)
Internal ML-seminars (covering broad ML topics, as well as domain-oriented)
We are looking for candidates who:
Have experience and/or interest in developing Reinforcement Learning algorithms
Have at least one year of professional experience
Know Python, have at least basic knowledge of ML frameworks (PyTorch, TensorFlow, Pandas, SciKit-Learn,.), and have experience in shipping and maintaining ML models in production
Developed ML models with real data that deviate from the standard, well-developed datasets used in research
Have a good knowledge of machine learning techniques, in particular, those used in decision making (classification/regression problems, bandits, model-free and model-based reinforcement learning)
Know the methodology of conducting scientific research and the use of the iterative process of conducting experiments
Have experience with training machine learning models in a distributed cloud environment will be an advantage (e.g. Google Cloud Platform, Kubernetes)