Мы используем технические cookie и статистику посещений: Яндекс Метрику и собственный обезличенный журнал Zorky (cookie zk_aid). Не собираем содержимое форм, текст поиска и полный IP; данные не продаём. Отказаться можно кнопкой ниже, а также через Global Privacy Control или Do Not Track в браузере. Подробнее о cookie и статистике.
Zorky CRMZorky CRM
EN|RU
@termdocs
← Все вакансии

[T04] Machine Learning Engineer (ML) - Permanent Role

senior5,500 SGD · период не указанSingapore, SGСкор 72.5/1003нед назад
Аналитика рынка
📊 AI / ML / DS: зарплаты и спрос на рынке
Стек
API DevelopmentLiaising with cross functional teamsCollaborate With EngineersBusiness OptimizationDesignlarge datasetsData WranglingStatistical Analysis SoftwareTask CompletionModel EvaluationModel TrainingEngaging Stakeholders
Откликнуться
Загрузите резюме — мы свяжем вас с работодателем напрямую через нашу базу.
Отправить резюме →
Описание
We are seeking an experienced Senior Data Scientist / Machine Learning Engineer to join our dynamic team. As a Senior Data Scientist / Machine Learning Engineer, you will play a key role in analyzing and presenting data, developing and implementing machine learning models and algorithms to solve complex business problems. Your expertise will contribute to enhancing the delivery service of analytics solutions and products to our customers. Job Responsibilities Data analysis and insights: Perform exploratory data analysis, generate insights, and present findings to stakeholders. Use statistical methods and visualization techniques to communicate complex concepts and patterns effectively. Develop and deploy machine learning models: Design, build, and optimize machine learning models and algorithms to solve specific business problems. Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models into production environments. Model training and evaluation: Train and fine-tune machine learning models using appropriate algorithms and techniques. Evaluate model performance and identify areas for improvement, employing techniques such as cross-validation, hyper parameter optimization, and ensemble methods. Model deployment and integration: Collaborate with software engineers and DevOps teams to deploy machine learning models into production environments. Implement APIs and integrate models with existing systems and applications to enable real-ti
Контакты работодателя (email/phone/telegram) скрыты из публичного превью — отправьте резюме, чтобы мы связали вас напрямую.
Срочный вопрос? Напишите @termdocs