Research Engineer focused on large-scale LLM training infrastructure, optimizing distributed training strategies, system reliability, and performance across GPU clusters. The role involves bridging research and production deployment for AI foundation models.

Research Engineer focused on the reliability and performance of AI training systems, including distributed training, reinforcement learning frameworks, and high-performance inference for large foundation models. Responsibilities include building observability tools, managing cluster governance, and optimizing resource utilization.

Research Engineer focused on building and optimizing distributed reinforcement learning systems and infrastructure for large-scale AI foundation models. This role involves designing end-to-end RL pipelines, optimizing training performance on GPU clusters, and collaborating with researchers on system-algorithm co-design.

Research Engineer focused on building and optimizing large-scale distributed training infrastructure for foundation models, including multimodal LLMs and image/video generation models. This role involves deep expertise in parallelism strategies, system reliability, and performance optimization on large GPU clusters, bridging research and production deployment.

Research Engineer focused on AI for 3D digital content creation, specifically human face and body, involving generative models and representations like NeRF. The role involves research, development, and transferring technology to products.

Research Scientist role focused on operations research for AI-native data infrastructure, including next-generation databases, AI for infra optimization, and LLM-based tooling. The role involves designing and optimizing vector indexing algorithms and exploring AI integration into operations research pipelines.

Research role focused on designing and developing AI-powered video codec algorithms, optimizing performance, and pushing the boundaries of video coding technologies. The role involves foundational research into large models and next-generation standards for multimedia content.

Research and develop deep learning models for multimodal data fusion using sEMG, computer vision, and IMU technologies, focusing on signal acquisition, processing, and handling sensor noise for enhanced human-virtual world interaction.

Research Scientist role focused on building AI-native data infrastructure, including VectorDBs, AI for infrastructure optimization, and LLM Copilot tooling. The role involves research, design, development, and publishing in top academic conferences.

Research Scientist focused on designing and optimizing state-of-the-art vector indexing algorithms for large-scale similarity search, filtered search, and hybrid retrieval use cases, contributing to next-generation vector database infrastructure. The role involves research and development of ANN algorithms, optimization for performance, and collaboration with engineering for productionization, with a strong emphasis on academic publications and staying current with AI x systems research.

Machine Learning Engineer focused on NLP and Knowledge Graphs for TikTok E-commerce. Responsibilities include constructing massive product knowledge graphs to enhance feed ranking, recommendations, and ads, and collaborating with cross-functional teams on product strategies. Requires a Bachelor's degree, 3+ years of ML/NLP/CV experience, and proficiency in C++/Python/Go/Java.