Research Scientist Graduate (Seed Model - LLM) - 2026 Start (PhD)

About the role

About The Team: LLM team is dedicated to advancing the next generation of LLMs and solving fundamental challenges in LLM development. Our areas of focus include model pretraining, posttraining, inference, memory capabilities, learning, interpretability and other related directions. We dive deep into the latest technologies and create comprehensive solutions from concept to completion. In our endeavor to adopt LLMs in real-life scenarios, we explore methods to enhance applications through technological innovation. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

About Doubao (Seed): Established in 2023, the ByteDance Seed team is dedicated to pioneering new paths toward artificial general intelligence. We aspire to advance the frontier of intelligence to drive progress for both technology and society. With a long-term vision for the AI sector, the Seed team's research spans MLLM, GenMedia, AI for Science, and Robotics. We maintain a global presence with laboratories and career opportunities across China, Singapore, and the United States. To date, we have launched industry-leading general foundation models and cutting-edge multimodal capabilities. Our technology powers over 50 application scenarios — including Doubao, Jimeng, TRAE, Dola and Dreamnia — and serves enterprise customers through Volcano Engine and BytePlus. Third-party data shows that the Doubao App ranks first in user volume in the Chinese market, while Doubao foundation models lead the industry in average daily token consumption.

Responsibilities

• Explore large-scale models and optimize systems
• Data construction, instruction tuning, preference alignment, and model optimization
• Improving relevant model capabilities, such as reasoning, coding, and math, etc.
• In-depth research and exploration of future use cases

Qualifications

Minimum Qualifications

• Individuals who are completing or have recently completed a PhD degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
• Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc.

Preferred Qualifications

• Experience with large-scale model training, deep learning and machine learning algorithms are preferred
• Candidates who have led influential projects or papers in the field of large-scale models are preferred
• Excellent problem analysis and solving skills, able to deeply solve problems in large-scale model training and application
• Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress

Pay

The base salary range for this position in the selected city is $254,400 - $480,000 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

• Employees have day one access to medical, dental, and vision insurance
• 401(k) savings plan with company match
• Paid parental leave
• Short-term and long-term disability coverage
• Life insurance
• Wellbeing benefits
• 10 paid holidays per year
• 10 paid sick days per year
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)

Benefits may vary depending on the nature of employment and the country work location. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.