Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Чёткие обязанности, современный стек для ML и работы с данными и хороший пакет льгот делают вакансию привлекательной для начала карьеры, но широкий набор требований и отсутствие зарплаты оставляют вопросы к объёму роли и уровню оплаты.
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Широкий профильЗарплата не указанаСовременный стекХорошие льготы
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Engineer (Machine Learning/Data Analytics): Building and maintaining analytical solutions, predictive models, and machine learning pipelines across cloud and on-premises environments with an accent on production-level software, data processing, and automation. Focus on developing reliable analytical applications, integrating testing and deployment workflows, and solving complex data and customer requirements with data scientists and product teams.
hirify.global is a global data and technology company providing analytical solutions across financial services, healthcare, automotive, insurance, and other markets.
What you will do
Develop data analyses, predictive models, proofs of concept, and production-level analytical solutions.
Build and maintain machine learning pipelines for data ingestion, transformation, and model training.
Develop automation across analytical workflows to reduce operational costs and improve speed to market.
Test automated solutions, support application deployment, conduct code reviews, and produce technical documentation.
Translate client and customer requirements into analytical or technical solutions while collaborating with data scientists, product managers, and partner teams.
Identify automation opportunities, evaluate proposed improvements, and maintain current knowledge of analytical methods and software tools.
Requirements
At least 1 year of technical software development experience and production-level programming in Python, C++, or another general-purpose language.
Understanding of large-scale data processing technologies such as Hadoop and Spark, as well as graph and time-series databases.
Exposure to natural language processing and analysis of unstructured data.
Experience or familiarity with AWS, Azure, or Google Cloud Platform, plus Docker, Kubernetes, or OpenShift.
Back-end development skills, including REST APIs, and familiarity with Angular or React.
Advanced degree or equivalent in Machine Learning, Computer Science, Engineering, Physics, Statistics, Applied Mathematics, or a related field; fluent English required.
Culture & Benefits
Flexible working hours and home office options within the hybrid work model.
Professional growth through career pathways, learning programs, online courses, books, and training.
Social benefits including life insurance, food vouchers, additional health and dental insurance, flex allowance, and internet coverage.
Twenty-five paid vacation days, an additional birthday day off, and three paid days for social responsibility activities.
Additional benefits include corporate discounts, family allowances, a Multisport card, Sharesave plan, employee assistance program, and birthday gift.
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