Content Understanding Multimodal Model Algorithm Engineer-Global E-commerce-Soaring Star Talent[...]

Content Understanding Multimodal Model Algorithm Engineer-Global E-commerce-Soaring Star Talent Program Location: Team: Algorithm Employment Type: Regular Job Code: A A Share this listing: Responsibilities Team Introduction: Through algorithm optimization and collaboration with business teams, the team conducts comprehensive quality and ecosystem governance for ByteDance's e-commerce products. This involves combating risks, violations, and low-quality issues, as well as constructing and optimizing a healthy e-commerce ecosystem. 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. 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. 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. The model should also achieve high-accuracy autonomous decision-making and interpretable COT generation, significantly reducing misjudgments. 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." Ultimately, the large language model-based intelligent moderation system should approach or exceed human moderators' accuracy and evolve toward fully automated review. Project Content: Research on e-commerce intelligent moderation multimodal large language models includes, but is not limited to: Modality fusion: Enhance fine-grained understanding of text, audio, image, video, and live-streaming data to enable high-accuracy autonomous decision-making and interpretable COT generation. Few-shot capabilities: Address e-commerce multilingual, long-sequence, and few-shot challenges, strengthen Few-Shot/Zero-Shot capabilities, and enable complex instruction and auto-prompt generation for dynamic business rules. Adversarial defense: Study AIGC image/video discrimination to enhance the review model's ability to defend against vague and abstract generated content. Agent capabilities: Enable RAG module invocation, tool usage, and Auto-planning; improve the model's dynamic reasoning and reflection abilities. Involved Research Directions: Large language models, multimodal large language models, Few-shot learning, AIGC decision-making, AIGC data generation, reinforcement learning, Agent Qualifications Got doctor degree, preferably with a background in artificial intelligence, computer science, or mathematics. Possess solid programming skills, a strong foundation in data structures and algorithms, and proficiency in using various algorithmic and engineering frameworks. Prior publications in international conferences or journals (including but not limited to ACL, EMNLP, NeurIPS, ICML, ICLR, CVPR) are preferred. Strong foundation in machine learning, with in-depth understanding and research experience in deep learning, reinforcement learning, NLP, or multimodal learning. Demonstrate good communication and collaboration skills, with the ability to work closely with the team to explore new technologies and drive technical innovation. Job Information About Us Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. Why Join ByteDance Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day. As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us. Diversity & Inclusion ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. #J-18808-Ljbffr