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Build and deploy production-grade ML models for marketing and personalization at a fast-growing digital bank, solving complex business problems with AI.
At Vio, we believe booking accommodation should feel fair and effortless, never overwhelming or unclear. As one of the world's fastest-growing travel tech platforms, we help millions of users make smarter travel…
Builds and optimizes large-scale data pipelines and storage systems for TikTok’s recommendation engine using Java, Spark, Flink, and Kafka.
Build and optimize large-scale recommendation system architectures using big data tools like Spark and Flink to process and analyze user data for TikTok’s AI-driven content feeds.
Build and deploy AI-powered applications using LLMs, vector databases, and AI orchestration frameworks like LangChain or Semantic Kernel.
Build and deploy AI-powered software solutions, integrating ML models (PyTorch/TensorFlow) with full-stack development in Python and cloud platforms like Azure.
Design and build scalable data infrastructure for a media company, including data lakes, customer platforms, and AI-powered analytics to drive audience and business decisions.
Design and build scalable data infrastructure, pipelines, and AI-powered analytics for a media company, enabling data-driven decisions across subscriptions, advertising, and editorial.
Lead the design and scaling of data infrastructure for a media business, including data lakes, CDPs, and AI-powered analytics products that support editorial, subscriptions, and advertising teams.
Build and optimize scalable backend systems for TikTok Shop’s recommendation infrastructure, including data pipelines and high-performance services to power AI-driven product suggestions.
Build and optimize TikTok’s recommendation architecture, focusing on distributed systems, performance, and scalability to enhance user experience and system stability.
Builds and optimizes AI-driven recommendation systems using C/C++ and Python to improve user experience.
Builds and optimizes Huawei’s big-data stack, ETL pipelines, and search/recommendation systems using Spark, Hive, Hadoop, and Python/Java/Scala.
Build and maintain large-scale offline computing systems for TikTok’s recommendation architecture, using Flink, Spark, and AI stacks like PyTorch to power feeds for over 1 billion users.
Build and optimize TikTok’s recommendation system architecture to ensure high availability and performance for users.
Designs offline data architectures for TikTok’s large-scale recommendation systems, building scalable storage and computing systems while applying data mining and NLP to extract insights from big datasets.
Design and build offline computing systems for TikTok’s large-scale recommendation infrastructure using Java/Python and big-data tools like Flink and Spark.
Designs and optimizes large-scale recommendation systems using AI/ML, focusing on cost-efficiency, multimodal data, and adaptive tuning for e-commerce.
Build and optimize distributed orchestration frameworks for large-scale ML training and inference in Kubernetes, focusing on resource efficiency and next-gen recommendation systems.
Designs and builds scalable offline/real-time data pipelines and distributed storage for TikTok’s recommendation, search, and ads systems using batch and stream processing.
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