AI Engineer

We are a team of AI & Crypto researchers and engineers (coming from DeepMind, Google Web3, and other leading AI/Crypto companies) with the long-term mission of co-creating the full decentralized AI stack in a trustless and permissionless way, with fair compensation for participation and contribution, that advances and benefits all of humanity. Our first focus is on decentralizing Data and building personalize agents.

Our team is small, operating in a flat structure, highly motivated, and focused on engineering excellence. Eidon is a place for those who like to take ownership, have strong curiosity & do-it energy, appreciate challenging themselves, and are ready to work in the intersection of multiple knowledge areas. All employees are expected to be hands-on and to contribute directly to the mission of advancing decentralized AI. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers and researchers are expected to have strong listening and communication skills. Sharing knowledge openly, concisely, and accurately with teammates is a baseline requirement.

We are funded by top tier VCs from the Valley

Eidon AI is seeking a Machine Learning Engineer to develop and maintain our ML infrastructure while collaborating with our AI research team to implement cutting-edge algorithms that advance our decentralized network. The ideal candidate will bridge the gap between theoretical research and practical implementation, ensuring our ML systems are robust, scalable, and efficient.

• Design, develop, and maintain ML infrastructure and pipelines
• Implement complex ML algorithms in collaboration with AI researchers
• Optimize ML models for production deployment and scaling
• Build and maintain ML monitoring and evaluation systems
• Collaborate with the research team to translate theoretical advances into practical implementations
• Contribute to the development of novel ML solutions for decentralized systems

• Engineering background (e.g., CS, CE, or EE degree or equivalent experience)
• Strong experience in machine learning engineering and infrastructure
• Proficiency in ML frameworks (PyTorch, TensorFlow, etc.)
• Experience with ML deployment and monitoring tools
• Strong programming skills in Python and other relevant languages
• Experience with distributed computing and large-scale ML systems
• Knowledge of MLOps best practices and tools
• Familiarity with decentralized systems and blockchain technology is a plus
• Strong mathematical and algorithmic problem-solving skills
• Experience with cloud platforms and containerization

Open to candidates in the Bay Area.