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Machine Learning Engineer
Это объявление было просмотрено
Компания: Adrack
Локация: Yerevan, Армения
Крайний срок: 29 August 2020

ТИП ПОЛНОМОЧИЙ: 

Full Time

ОПИСАНИЕ ДОЛЖНОСТИ: 

Plat.ai LLC is looking for a Machine Learning Engineer to join its team.

ОБЯЗАННОСТИ: 

- Translate unstructured business problems into well-defined machine learning projects;
- Collaborate with a cross-functional team of product managers and developers to identify existing problems on time, prepare modeling solutions and apply them on real-time environment;
- Build and deploy models for real-time predictions;
- Build model performance monitoring tools, use the existing tools in the system to keep track of production level models' performance;
- Prepare documentation for custom models;
- Effectively communicate outcomes of analytics models to non-statistical audience.

ТРЕБУЕМАЯ КВАЛИФИКАЦИЯ: 

- Degree in a quantitative discipline;
- Relevant experience in doing ML work either in financial services or technology company is desired;
- Expert experience in designing, developing, and deploying machine learning models/ algorithms;
- Extensive programming experience in R or Python and an interest in learning new languages and technologies;
- Knowledge of data structures and data engineering solutions;
- Intermediate or upper level of English language.

ПРОЦЕДУРА ПОДАЧИ ЗАЯВОК: 

All interested candidates whose profile meets the mentioned requirements and are motivated to work in a hard-working and continuously learning-addicted family of data scientists, are welcome to send their CV to: ******.*@****.** by 29 August 2020 indicating the position title ("Machine Learning Engineer") in the subject line of the email.

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ДОПОЛНИТЕЛЬНЫЕ ЗАПИСИ: 

Perks and Benefits:
- Health insurance;
- Contribution to gym membership plan;
- Contribution to the costs associated with job-related continuous training and development.

О КОМПАНИИ: 

Plat.ai is a team of data scientists/ machine learning engineers who are utilizing the power of machine learning to solve existing problems of the clients and proactively designing new optimization tools.