About the team
The Seed Multimodal Interaction and World Model team is dedicated to developing models that have human-level multimodal understanding and interaction capabilities. The team is working to advance the exploration and development of multimodal assistant products.
Responsibilities
Develop multimodal foundation models integrating vision, language, audio, and environment signals.
Design and optimize world models for reasoning, planning, and interaction.
Build training pipelines including data curation, alignment, and reinforcement learning.
Improve agent capabilities such as perception, memory, decision-making, and tool use.
Explore next-generation interaction paradigms between humans and intelligent systems.Minimum Qualifications:
Individuals who are completing or have recently completed a Bachelor's 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 relevant areas.
Preferred Qualifications:
Experience in multimodal learning, reinforcement learning, or agent systems through internships is preferred.
Strong problem-solving and collaboration skills.
Numbers & Facts
Location
San Jose, CA
Skills
Algorithmsunmatched
C Programming Languageunmatched
C++ Programming Languageunmatched
Computer Engineeringunmatched
Computer Scienceunmatched
Data Structuresunmatched
Electrical Engineeringunmatched
Mathematicsunmatched
Memory Hardwareunmatched
Multimodal Interactionunmatched
Physicsunmatched
Problem Solving Skillsunmatched
Product Developmentunmatched
Python Programming/Scripting Languageunmatched
Reinforcement Learningunmatched
Scientific Researchunmatched
Team Playerunmatched
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