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Research Scientist in Foundation Model; Seed - LLM - Model

Job in San Jose, Santa Clara County, California, 95111, USA
Listing for: ByteDance
Full Time position
Listed on 2026-02-17
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer
  • Research/Development
Job Description & How to Apply Below
Position: Research Scientist in Foundation Model (Seed - LLM - Model)
Established in 2023, the Byte Dance Seed team is dedicated to discovering new approaches to general intelligence, and pursuing the edge of intelligence. Our research spans large language models, Gen Media, AI for Science, Robotics and more. With a long-term vision and determination in AI, the Byte Dance 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 Responsibilities:
-Solid foundation in data structure and algorithm design, proficient in Python/C++, proficient in deep learning frameworks such as PyTorch and Tensor Flow, proficient in distributed large language model training framework such as Megatron/FSDP/Deepspeed.

-Good reading and writing skills and a solid foundation in mathematics.

-Strong sense of responsibility, proactive, with good communication and teamwork skills.

-Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

Minimum Qualifications:

-Pre-trained basic technologies, including efficient training and encapsulated deployment services, NLP, CV, video, Multi Modal Machine Learning and other related pre-trained models and their downstream applications are preferred.

-Candidates who have published papers in top academic conferences, and have achieved excellent results in competitions in the fields of Multi Modal Machine Learning, Computer Vision, or Machine Learning are preferred.
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