AI Research Scientist in LLM-based Agent

United States

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ChainOpera AI is the world’s first truly decentralized and open AI platform for simple, scalable, and trustworthy collaborative AI economy, and the AI app ecosystem for accessible and democratized AI - our GPUs, our model, our personal AI.

ChainOpera AI is supported by

  • Enterprise-level generative AI platform for system scalability, model performance, and security/privacy (ChainOpera AI Platform)

  • Leading open source library in large-scale distributed training, model serving, and federated learning (FedML)

  • Innovative and unique edge-cloud collaborative AI models and systems towards on-device personal AI (Fox LLM)

  • Internet veterans for serving billion-level end users based on cloud computing and mobile internet

  • Established researchers in blockchain, machine learning, and large-scale distributed systems (80000+ citations)

  • Ecosystem partnership with GPU providers, model developers, AI platforms, and AI applications

  • Top-tier investors, angels, and advisors

Responsibilities:

  • Design and develop novel architectures for LLM-based agents that can reason, plan, and execute tasks autonomously

  • Research and implement advanced techniques for improving agent capabilities, including multi-task learning, few-shot learning, and continual learning

  • Investigate methods for enhancing the reliability, safety, and ethical behavior of LLM-based agents

  • Develop strategies for efficient integration of external knowledge and tools with LLM agents

  • Collaborate with blockchain and distributed systems experts to explore decentralized agent architectures

  • Publish research findings in top-tier AI conferences and journals

  • Work closely with engineering teams to prototype and deploy research outcomes

Requirements:

  • Ph.D. in Computer Science, Artificial Intelligence, or a related field

  • Strong background in natural language processing, deep learning, and reinforcement learning

  • Experience with large language models and their applications

  • Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)

  • Excellent problem-solving skills and ability to think creatively about AI agent architectures

  • Strong publication record in top-tier AI conferences or journals

Preferred Qualifications:

  • Experience with multi-agent systems and collaborative AI

  • Knowledge of cognitive architectures and symbolic AI approaches

  • Familiarity with blockchain technologies and decentralized systems

  • Track record of open-source contributions to AI projects, particularly in the field of language models or AI agents

  • Experience mentoring junior researchers or leading research projects in AI

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture Blockchain Computer Science Deep Learning Distributed Systems Engineering Generative AI GPU LLMs Machine Learning NLP Open Source Privacy Python PyTorch Reinforcement Learning Research Security TensorFlow

Perks/benefits: Conferences

Region: North America
Country: United States

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