ML Engineer with Python knowledge

23 марта 2020    66
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Requirements:
— 3+ years of Python engineering and experience in research and development of machine learning and deep learning technologies for real-world products
— Experience of deploying and maintaining machine learning models in production
— Experience with time series analysis
— Experience writing, maintainable, testable, production-grade Python code
— Understanding of different machine learning and deep learning algorithm families and their tradeoffs
— Experience with deep learning libraries and frameworks (Scikit-learn, XGBoost, TensorFlow, Keras, PyTorch, etc.)
— Good knowledge of ML/DL theoretical underpinnings
— Team-player with strong interpersonal skills

Will be a plus:
— Experience of deploying and maintaining machine learning data pipelines in production
— Airflow experience will be a big plus
— Experience with large-scale machine learning (100GB+ datasets)
— Competitive machine learning experience (e.g. Kaggle) could be a plus

We offer multiple benefits, that include:
— Challenging work in an international professional environment
— The long-standing team as this is for a long term project
— Competitive salary
— Flexible work-from-home & remote work policy
— Mastering English language with a native speaker
— 40-hours working week with flexible working hours
— PE accounting and support
— 20 paid vacation days per year
— 14 paid sick leaves per year
— Collaborative friendly team environment
— Cozy fully equipped office space in the city center

Responsibilities:
— Build, maintain, and improve our price large-scale forecasting algorithms and their underlying systems from scratch. Currently, we are in the process of building a new set of services for our new e-commerce analysis platform built on top of AWS/MWS
— Implement end-to-end solutions for batch and real-time algorithms
— Build tooling around monitoring, logging, automated testing, and A/B testing
— Collaborate with your peers and other teams to teach, learn and execute efficiently
— Contribute to improving our processes and engineering culture

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