Student Researcher (Doubao (Seed) - LLM Foundation Research)- 2025 Summer/Fall/Winter (PhD)

ByteDance • San Jose, CA

101d

About The Position

This position is responsible for researching and building the company's LLMs. The role involves exploring new applications and solutions for related technologies in areas such as search, recommendation, advertising, content creation, and customer service. The goal is to meet the increasing demand for intelligent interactions from users and to significantly enhance their lifestyle and communication in the future. The Student Researcher position provides unique opportunities that go beyond the constraints of our standard internship program, allowing for flexibility in duration, time commitment, and location of work. The Student Researcher program offers a flexible format that can accommodate both Onsite and Remote arrangements, as well as Part-Time or Full-Time commitments, depending on the needs of the project and the researcher. We are looking for talented individuals to join us for a Student Researcher opportunity in 2025. Student Researcher opportunities aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

• Design advanced reinforcement learning algorithms for large language models by integrating technologies such as heuristic-guided search, multi-agent reinforcement learning, and other related techniques.
• Formulate a novel reward modeling methodology aimed at significantly enhancing robustness, improving generalization capabilities, and increasing overall accuracy.
• Develop scalable oversight mechanisms that enable efficient monitoring and control of LLMs as they grow in size and complexity, ensuring consistent alignment with predefined objectives.
• Focus on enhancing the interpretability of language models, ensuring that their decision-making processes and outputs are transparent and understandable to users and stakeholders.
• Enhance reasoning and planning throughout the entire development process, encompassing data acquisition, model evaluation, pretraining, SFT, reward modeling, and reinforcement learning, to bolster overall performance.
• Synthesize large-scale, high-quality (multi-modal) data through methods such as rewriting, augmentation, and generation to improve the abilities of foundation models in various stages (pretraining, SFT, RLHF).
• Solve complex tasks via system 2 thinking, leverage advanced decoding strategies such as MCTS, A*.
• Investigate and implement robust evaluation methodologies to assess model performance at various stages, unravel the underlying mechanisms and sources of their abilities, and utilize this understanding to drive model improvements.
• Teach foundation models to use tools, interact with APIs and code interpreters. Build agents and multi-agents to solve complex tasks.

What This Job Offers

• Career Level: Intern
• Industry: Publishing Industries
• Number of Employees: 5,001-10,000 employees