LLM Research Scientist - Next-Gen Models & Innovation

ByteDance; San Jose (CA); On-site; USD 212,800 - 387,600; Full time

Benefits offered by this job

Medical, dental & vision insurance

401(k) with company match

Paid parental leave

Disability & life insurance

Wellbeing benefits

10 paid holidays per year

10 paid sick days per year

17 days Paid Personal Time

Job summary

ByteDance's Seed LLM team is seeking a student intern to contribute to large-scale model research, data preparation, and model optimization in California. The role emphasizes hands-on work across pretraining, posttraining, inference, memory, and interpretability with collaboration across teams.

The candidate should be pursuing a degree in CS, mathematics, or engineering, with completion by 2027, strong coding skills in C/C++ or Python, and an interest in LLM-related projects.

Qualifications

• Pursuing a Bachelor's or Master's degree with expected graduation in 2027 and onboarding by end of 2027.
• Excellent coding ability, data structures and fundamental algorithms; proficient in C/C++ or Python.
• Interest or project experience in LLM-related areas (training, evaluation, applications).

Responsibilities

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

Skills

C/C++

Python

Data structures & algorithms

Education

Bachelor's or Master's in CS/Math/Engineering

Job description

ByteDance's Seed LLM team is seeking a student intern to contribute to large-scale model research, data preparation, and model optimization in California. The role emphasizes hands-on work across pretraining, posttraining, inference, memory, and interpretability with collaboration across teams.

The candidate should be pursuing a degree in CS, mathematics, or engineering, with completion by 2027, strong coding skills in C/C++ or Python, and an interest in LLM-related projects.