Research Jobs in Web3

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:

• Develop and implement novel techniques for ensuring the safety and robustness of AI systems, particularly in decentralized environments

• Research methods for alignment of AI systems with human values and intentions

• Investigate approaches to make AI systems more interpretable, transparent, and accountable

• Design and conduct experiments to test the safety and reliability of AI models, especially large language models and autonomous agents

• Collaborate with blockchain experts to address unique safety challenges in decentralized AI systems

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

• Work closely with engineering teams to implement safety measures in our AI products

• Stay abreast of the latest developments in AI safety research and contribute to the global discourse on ethical AI

Requirements:

• Ph.D. in Computer Science, Artificial Intelligence, or a related field with a focus on AI safety

• Strong background in machine learning, deep learning, and AI ethics

• Experience with formal verification methods, robustness testing, and uncertainty quantification in AI systems

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

• Excellent analytical and problem-solving skills with a keen eye for potential risks in AI systems

• Strong publication record in top-tier AI conferences or journals, particularly in the field of AI safety

Preferred Qualifications:

• Experience with blockchain technologies and understanding of their implications for AI safety

• Knowledge of game theory and mechanism design as applied to AI systems

• Familiarity with regulatory frameworks and policy discussions surrounding AI development

• Track record of open-source contributions to AI safety projects or tools

• Experience mentoring junior researchers or leading research projects in AI safet