We are looking for a talented developer passionate about data engineering and machine learning to join our ML team. The team is responsible for automatization of critical business processes within the company. The challenges we are facing are productionizing our existing machine learning algorithms, development of a reliable, observable ML infrastructure, and building a data platform for the fancy Data Science mentioned above. Responsibilities: - Help us building our data infrastructure to allow rapid prototyping and data analysis; - Understand business objectives and develop systems that help to achieve them, along with metrics to track their progress; - Productionize and scale the pre-processing and feature engineering components; - Prepare ML models for production environment; -You will, sometimes develop, and also, sometimes, support our web APIs; - Verify data quality, and ensure it via data cleaning; - Research and implement some of the best practices to improve the existing machine learning infrastructure. Requirements: - At least an intermediate level of Python and good knowledge of at least one more object oriented language (preferably Java); - At least basic knowledge of Docker and its ecosystem; - Good knowledge of the OOP principles, design patterns and how to not overuse them; - If curl, sed, grep and cat are not some gibberish to you, we like it; - Git experience and associated workflows, we prefer GitFlow; - Writing code that can be trusted. We prefer tests with good coverage as proof; - We speak English, and so will you. We also write in English, even more than we speak, you got the point; - Outstanding analytical and problem-solving skills; - Good communication skills and ability to work in a team. Nice to have: - Knowledge of JS and functional programming fundamentals; - Some basic experience with machine learning libraries such as scikit-learn or Pytorch (we use it); - Mechanical sympathy, i.e. you care about what hardware is underneath your...

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