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описание
Fractal is a strategic AI partner to Fortune 500 companies that aims to support enterprise decision-making with artificial intelligence and human-centered innovation.
задачи
Design, train, and optimise machine learning models for user personalisation, including recommendation engines, ranking algorithms, user segmentation, and content analysis;
Build and maintain robust, scalable data pipelines for feature engineering and model training using structured and unstructured large-scale datasets;
Deploy and supervise ML models in production environments to ensure high availability, performance, and continued relevance;
Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement;
Collaborate with multidisciplinary teams to align machine learning initiatives with business objectives and user needs;
Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration into existing systems.
требования
Strong demonstrated experience with ML training frameworks, mainly TFX and Kubeflow Pipelines SDK, and model serving technologies such as TensorFlow Serving, Triton, and TorchServe;
Expertise in the full machine learning lifecycle, from model development, deployment, and serving to monitoring and maintenance;
Proficiency in Python and knowledge of ML libraries and frameworks such as TensorFlow and PyTorch;
Experience with high-volume data processing and real-time streaming architectures;
Strong understanding of recommendation system design and personalisation algorithms;
Familiarity with Generative AI and its applications in production settings;
Good communication and analytical problem-solving skills;
Nice to have: Experience working on OTT platforms, experience in Scala.
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