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Salary
≈ $23k – $62k per year (Estimated)
Location
Hybrid (Moscow, Russia)

Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 25, 2026. F6 scores A on the Alion truth index.

Overview
Company
Impact
Profile match

F6

F6 is a cybersecurity enterprise specializing in threat intelligence, cyberattack prevention, fraud detection, and digital crime investigation. Headquartered in Moscow, Russia, the company provides an ecosystem of software solutions and managed security services designed to neutralize complex cyber threats and financial crimes. Its core offerings include attribution-based Threat Intelligence platforms, online Fraud Protection, Managed Extended Detection and Response (MXDR), and Attack Surface Management (ASM).

F6, ведущий разработчик технологий для борьбы с киберпреступностью. Мы разрабатываем высокотехнологичные решения для защиты от киберугроз и объединяем экспертов, которые стремятся сделать мир безопаснее. Сейчас мы в поиске ML-разработчика.

ЗАДАЧИ, КОТОРЫЕ ПРЕДСТОИТ РЕШАТЬ:

  • Разработка и внедрение моделей машинного обучения для семантического анализа текстовых и веб-данных.

  • Построение систем автоматической категоризации и кластеризации контента на основе неструктурированных источников.

  • Разработка алгоритмов для генерации кратких текстовых представлений (summary / description) с использованием NLP-подходов.

  • Проектирование и оптимизация моделей, работающих с слабо структурированными и шумными данными.

  • Построение и анализ графовых представлений данных, выявление связей и закономерностей.

ОТКЛИКАЙСЯ НА ЭТУ ВАКАНСИЮ, ЕСЛИ У ТЕБЯ ЕСТЬ:

  • Практический опыт работы с фреймворками: PyTorch, TensorFlow, Keras.
  • Понимание архитектур сверточных нейронных сетей: ResNet, EfficientNet, DenseNet.
  • Опыт построения нейронных сетей с нуля и адаптации предобученных моделей.
  • Опыт работы с несбалансированными выборками и задачами многоклассовой классификации.
  • Практический опыт применения классических алгоритмов машинного обучения на табличных данных (scikit-learn).
  • Опыт анализа и предобработка данных с использованием pandas, NumPy.
  • Feature engineering, оценка и валидация моделей.
  • Опыт построения ETL-пайплайнов для обработки данных и подготовки к обучению моделей.
  • Опыт очистки, трансформации и подготовки данных для ML-задач.
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