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Machine Learning Researcher

Ziggy Staffing LLC
San Francisco, CA Full Time
POSTED ON 2/12/2025
AVAILABLE BEFORE 4/28/2025

About Us :

We are on a mission to create the world's first AI-powered decentralized network that scales, secures, and delivers cutting-edge machine learning capabilities. Our vision is to make AI globally accessible, unbiased, and evergreen. Backed by industry leaders and a16z, we are looking for passionate researchers to drive innovation in AI and blockchain.

Key Responsibilities :

  • Conduct research to advance the scalability and efficiency of machine learning in a decentralized system.
  • Explore sparsification and other techniques to ensure models remain current and competitive.
  • Translate cutting-edge research into implementable solutions, bridging theory and practice.
  • Collaborate with engineers to optimize model training and inference for production.
  • Contribute to the development of consensus mechanisms and network security.

Must-Have Qualifications :

  • Strong academic or industry background in machine learning research.
  • Ability to read, interpret, and implement findings from research papers.
  • Proficiency in Python, with experience in developing scalable algorithms.
  • Understanding of blockchain fundamentals and consensus algorithms.
  • Proven track record of publishing or contributing to technically complex projects.
  • Nice-to-Have Qualifications :

  • Advanced degree (MS / PhD) with relevant research in machine learning.
  • Experience in sparsification or related areas, with publications in the field.
  • Familiarity with Rust and Solana architecture.
  • Contributions to open-source blockchain or machine learning projects.
  • Why Join Us?

  • Work on groundbreaking research that bridges AI and blockchain.
  • Collaborate with a world-class team of engineers, researchers, and innovators.
  • Shape the future of decentralized AI, impacting global accessibility and security.
  • Competitive compensation, equity options, and career growth in a high-impact field.
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