Senior Machine Learning Researcher @ RTB House

• 4+ years of hands-on experience with Machine Learning / Data Science
• Interest and willingness to constantly develop in the area of ​​Machine Learning
• Knowledge of statistics and probability
• Proficiency in programming

Selected technologies used:

• Python, Java, Scala
• PyTorch, NumPy, Pandas
• Jupyter Notebooks

Additional advantages will be:

• Experience in the ML industry
• Experience in designing recommendation systems
• Practical knowledge of the tools we use

Sample topics:

• Implementation and analysis of new model architectures, such as convolutional networks, transformer
• Analyze the difference in the distribution of training and production data. Estimating the scale of the problem, identifying the best solution, analysis, implementation, deployment
• Experiments with the use of transfer learning
• A completely new approach to generating product recommendations that is free from proxy targets and uses contrastive loss function

We Offer:

• A very attractive salary
• Work in a team of enthusiasts with experience in machine learning who willingly share their knowledge and skills
• Extremely flexible cooperation conditions - you work when it is convenient for you and devote as much time as you can; you can work fully remotely
• Access to the latest technologies and the possibility of real use of them in a large-scale and highly dynamic project;
• Possibility of using the possessed knowledge and competences in practical applications - while optimizing algorithms supporting hundreds of millions of Internet users and monthly buyers of billions of advertising views in the RTB model, based on extensive data sets
• The effects of your work immediately visible in the companys business results
• Possibility to publish your results

,[Designing and implementing models, most often of deep neural networks, used to predict the behavior and preferences of Internet users, Analysis of the latest works in the field of Machine Learning, Conducting and analyzing A/B tests of new solutions, Developing and testing new approaches to modeling key issues, such as bidding in first-price auctions] Requirements: Python, Machine learning, TensorFlow, Scala, Java, PyTorch, NumPy, pandas, Deep learning Tools: YouTrack, DokuWiki, GIT, Gerrit, GitHub, Jenkins, Agile, Kanban. Additionally: Training budget, Flat structure, International projects, In-house trainings, Team Events, English lessons.

Kategorie

artificialIntelligence