Research Scientist - Seed Multimodal Interaction and World Model - Reinforcement Learning Focus

Responsibilities

About Seed Team Established in 2023, the ByteDance Seed team is dedicated to discovering new approaches to general intelligence, and pursuing the edge of intelligence. Our research spans large language models, speech, vision, world models, AI infrastructure, next-generation interfaces and more. With a long-term vision and determination in AI, the ByteDance Seed team remains committed to foundational research. We aim to become a world-class AI research team that drives real technological progress and delivers societal benefits. With labs across China, Singapore, and the U.S., our team has already released industry-leading general-purpose large models and advanced multimodal capabilities, powering over 50 real-world applications — including Doubao, Coze, and Jimeng.

• Design and implement reinforcement learning (RL) training systems for large-scale multimodal foundation models
• Develop unified modeling frameworks that integrate video, audio, and language, with a focus on visual latent reasoning
• Explore Reinforcement Learning-based approaches to bridge understanding and generation for multimodal visual reasoning
• Collaborate with researchers to evaluate models on tasks involving world modeling, reasoning, and instruction-conditioned generation

Qualifications

Minimum Qualifications:

• Master or PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline
• Publications in top-tier venues, such as CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML, or other leading conferences in AI and ML
• Strong research background in at least one of the following: reinforcement learning, multimodal learning, video understanding, or vision-language modeling

Preferred Qualifications:

• Experience with reinforcement learning in multimodal or interactive environments
• Familiarity with video generation or diffusion-based generative models
• Experience with large-scale model training (e.g., distributed training, curriculum learning, or memory-augmented transformers)
• Solid programming and engineering skills, with experience building training or evaluation pipelines for ML models

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $198360 - $416100 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.