Large Model Application Algorithm Research Scientist - International Content Security Algorithm Research - Soaring Star Talent Program

Role Overview

The International Content Security Algorithm Research Team at ByteDance is dedicated to developing machine learning models and information systems that promote a safe and reliable environment across global products. Their work focuses on early risk detection, rapid incident response, and efficient threat monitoring while spearheading the advancement of foundational large models that support various platform functionalities such as content moderation, search, and recommendation.

Research Context and Challenges

Large Language Models (LLMs) have seen substantial progress in natural language processing and AI, excelling in generation, question answering, and translation. However, enhancing their reasoning capabilities remains a prime challenge, traditionally requiring costly Supervised Fine-Tuning (SFT) data. Innovative methods, including those from OpenAI, have extended chain-of-thought reasoning, but scaling these methods in practice presents difficulties.

Alternative approaches like Process-based Reward Models (PRM), Reinforcement Learning (RL), and Monte Carlo Tree Search (MCTS) have been investigated with varying success. Recent studies show that RL could potentially enable LLMs to autonomously develop superior reasoning skills without reliance on high-cost SFT data.

Key challenges include:

• Designing adaptable and precise reward models during reinforcement learning that reflect reasoning effectiveness and evolve throughout training.
• Ensuring stable training processes in RL environments, which are prone to instability due to extensive exploration when quality data is scarce.
• Extending RL-based reasoning from areas rich in chain-of-thought data like mathematics and coding to more complex natural language tasks, necessitating novel data and methodological innovations.
• Optimizing reasoning efficiency to balance cost and quality, potentially leveraging knowledge distillation techniques or enhancing short-chain-of-thought models.

Qualifications

• PhD in Computer Science, Electronics, or a related discipline.
• Significant expertise in Machine Learning, Computer Vision, Natural Language Processing, or Recommendation Systems.
• Active involvement in relevant competitions or industry projects in ML, data mining, CV, NLP, or multimodal domains.
• Published research in prominent conferences such as KDD, WWW, NIPS, ICML, CVPR, ACL, AAAI, or similar.

Preferred Attributes

• Experience with research or development related to large models or reinforcement learning.
• Contributions to large model projects within open-source communities.
• Practical experience deploying large models in commercial settings.
• Proficiency in Python, C++, or other pertinent programming languages.
• Exceptional analytical and problem-solving capabilities with a passion for challenging technical issues.
• Strong enthusiasm for technology coupled with excellent communication and teamwork skills.

About ByteDance

Founded in 2012, ByteDance seeks to inspire creativity and enrich people's lives through its wide range of products including TikTok, Lemon8, CapCut, Pico, and various China-specific platforms such as Toutiao and Douyin. The company values innovation, curiosity, humility, and impactful collaboration in a fast-evolving technology landscape.

Diversity and Inclusion

ByteDance is committed to fostering a workplace that values diversity, where employees' skills, experiences, and perspectives from around the globe are respected. The company aims to reflect the diverse communities it serves and promote inclusive collaboration across its teams.