Content Understanding Multimodal Model Algorithm Engineer-Global E-commerce job opportunity at Tiktok.

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Tiktok Content Understanding Multimodal Model Algorithm Engineer-Global E-commerce
Experience: 1-year
Pattern: full-time
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Salary:
Status:

Engineer

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degreePhD
Singapore

Responsibilities Team Introduction: Through #algorithm optimization and #collaboration with business teams, the team conducts comprehensive quality and ecosystem governance for e-commerce products, #Enhancing platform integrity. This involves combating risks, violations, and low-quality issues, as well as constructing and optimizing a healthy e-commerce ecosystem while #Fostering innovation. The team aims to maximize platform governance effectiveness while improving operational efficiency and reducing costs. Additionally, the team is dedicated to advancing cutting-edge AI technologies to drive business transformation and development through technical innovation, covering diverse fields including but not limited to NLP, CV, multimodal models, large models, graph algorithms, and sequence algorithms. Project Objectives and Rationale: Intelligent content moderation in e-commerce is a highly complex field requiring #Sophisticated solutions. As moderation technologies continue to evolve, various domains are encountering new risks and adversarial content, which pose fresh challenges for the application of foundation models. For example, existing open-source foundation models underperform in E-commerce moderation tasks involving PBR changes, long text, long sequences, multilingual content, few-shot scenarios, and AIGC-generated adversarial content, #Demanding more effective models. Consequently, there is an urgent need to develop foundation models specifically tailored for intelligent e-commerce moderation to improve their effectiveness and adaptability in e-commerce governance. In particular, we must explore high-quality data auto-generation, efficient MOE Embedding, Auto-prompt generation, high-quality COT output, and foundation model knowledge distillation, #Driving business growth. __ The model should also achieve high-accuracy autonomous decision-making and interpretable COT generation, significantly reducing misjudgments, #Improving customer experience. For dynamic PBR changes, it should automatically retrieve similar moderation cases via RAG modules, decompose complex PBRs into simple atomic tasks, split rejection and exemption tasks, and auto-invoke corresponding tools, establishing an industry-leading intelligent review system that knows to reject and why, #Setting new standards. Qualifications 1. Got doctor degree, preferably with a background in artificial intelligence, computer science, or mathematics. 2. Possess solid programming skills, a strong foundation in data structures and algorithms, and proficiency in using various algorithmic and engineering frameworks. 3. Prior publications in international conferences or journals (including but not limited to ACL, EMNLP, NeurIPS, ICML, ICLR, CVPR) are preferred. 4. Strong foundation in machine learning, with in-depth understanding and research experience in deep learning, reinforcement learning, NLP, or multimodal learning. 5. Demonstrate good communication and collaboration skills, with the ability to work closely with the team to explore new technologies and drive technical innovation.

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