Research Scientist Graduate, LLM)
ByteDance
This job at a glance
- Who can apply
- New grads, no experience needed
- Must know
- LLMsOnboardingPythonC++CData structures & algorithms
- Nice to have
- Machine learningDeep learning
- Work
- On-site in San Jose
- Pay
- Not stated by the employer.
- Skill demand
- Python27%LLMs8%C++3%of 99 similar entry-level jobs posted in the US this week
- Listed
- Oct 27, 2026 · still open
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About the Team
The Seed 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.
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.
About the Role
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.
Key Responsibilities
- Explore large-scale models and optimize systems.
- Data construction, instruction tuning, preference alignment, and model optimization.
- Improving relevant model capabilities, such as reasoning, code, math etc.
- In-depth research and exploration of future use cases.
Minimum Qualifications
- Individuals who are completing or have recently completed a BS 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.
- Demonstrated interest or project experience in LLM-related areas such as training, evaluation, or applications.
Preferred Qualifications
- Individuals who are completing or have recently completed an MS degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
- Experience with machine learning, deep learning, or large-scale models through internships is preferred.
- Strong problem analysis and problem-solving skills and good communication and collaboration skills, with the ability to learn quickly and work effectively in a team.
Job Information
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.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
Applications will be reviewed on a rolling basis - we encourage you to apply early.