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 novel algorithms and architectures for distributed and decentralized inference of large-scale AI models

  • Design and implement techniques to optimize inference speed, reduce latency, and improve resource utilization in decentralized environments

  • Collaborate with blockchain experts to integrate AI inference protocols with distributed ledger technologies

  • Conduct cutting-edge research at the intersection of AI, distributed systems, and blockchain technology, with a focus on inference optimization

  • Publish research findings in top-tier conferences and journals

  • Work closely with engineering teams to transition research prototypes into production-ready inference systems

  • Stay current with the latest advancements in AI, particularly in the areas of model compression, quantization, and efficient inference techniques

Requirements:

  • Ph.D. in Computer Science, Machine Learning, or a related field

  • Strong background in machine learning, deep learning, and distributed systems, with a focus on model inference

  • Experience with large-scale model deployment and optimization techniques

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

  • Familiarity with distributed computing frameworks and edge computing technologies

  • Excellent problem-solving skills and ability to think creatively about inference optimization

  • Strong publication record in top-tier AI conferences or journals, particularly in the area of efficient model inference

Preferred Qualifications:

  • Experience with blockchain technologies and decentralized systems

  • Knowledge of model compression techniques, quantization, and hardware-aware neural architecture search

  • Familiarity with edge AI and IoT deployments

  • Track record of open-source contributions to AI or distributed systems projects related to model inference

  • Experience mentoring junior researchers or leading research projects in the field of efficient AI inference

Location

United States

Job Overview
Job Posted:
2 days ago
Job Expires:
Job Type
Full Time

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