Machine Learning Engineer, E-Commerce Governance and Experience - USDSTikTok USDS Joint Venture • United States
Machine Learning Engineer, E-Commerce Governance and Experience - USDS
TikTok USDS Joint Venture
- United States
- United States
À propos
TikTok USDS Joint Venture is focused on enhancing user experience on its e-commerce platform through advanced AI systems. The Machine Learning Engineer will design and implement models that analyze user feedback and improve governance and experience across multiple channels.
Responsibilities : • Develop LLM-based CCR/VOC Models: Design and implement LLM-based CCR/VOC models, to cover user feedback from multiple channels, including reviews, after-sales service, customer service conversations, and tNPS, etc. Based on a 100+ intent classification system, identifies the users feedback intent accurately. • Apply Advanced LLM Techniques: Utilize state-of-the-art LLM post-training techniques, such as instruction tuning, Reinforcement Learning from Human Feedback (RLHF), and continuous learning, to optimize the system with minimal labeled data. • Build Robust Training Datasets: Identify challenging user feedback scenarios—including logistics inquiries, merchant issues, and platform-related problems—and construct specialized datasets to enhance AI model training. • Enable Multilingual and Multicultural Support: Build AI models capable of recognizing user feedback across diverse languages and cultural backgrounds, ensuring accurate semantic understanding for a global audience. • Optimize Model Efficiency and Deployment: Research and apply model compression, quantization, and efficient inference techniques to ensure the AI assistant operates at scale with low latency and high reliability. • CCR/VOC RCA Agents: Focusing on pain points in CCR, such as the need for rapid implementation of new labels and inefficient CCR problem handling processes in business side, this project leverages the agents autonomous interaction and intelligent decision-making capabilities to optimize existing models and processes. Through scenario-based training and iteration, the agent becomes a highly efficient assistant for CCR operations, solving the problems of slow response and low conversion rates in traditional models, and improving service quality and customer experience.
Qualifications : Required : • Bachelors degree in Computer Science or a related technical field. • 1+ years of professional experience in one or more of the following fields: Machine Learning, Natural Language Processing (NLP), or Computer Vision. • Proficiency in software development with at least one of the following programming languages: C++, Python, Go, or Java.
Preferred : • Experience in fine-tuning, distillation, or reinforcement learning for large language models in conversational AI applications. • Proficiency in multilingual NLP, machine translation, and cross-lingual dialogue modeling. • Experience in developing and optimizing e-commerce video and product multimodal large models, combining LLMs with video/product representations to support tasks like multimodal classification, video QA, and cross-modal retrieval. • A strong understanding of e-commerce policies, dispute resolution workflows, and merchant-buyer interactions to inform AI service design. • Expertise in AI agents, Retrieval-Augmented Generation (RAG), Mixture of Experts (MoE), sparse attention, reinforcement learning, and inference-time scaling. • Experience with distributed model training, low-latency inference, and deploying models efficiently.
Company :
Founded in , the company is headquartered in , , with a team of 1001-5000 employees. The company is currently Late Stage.
Compétences linguistiques
- English
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