ML Research Engineer
Machine intelligence will soon take over humanity’s role in knowledge-keeping and creation. What started in the mid-1990s as the gradual off-loading of knowledge and decision making to search engines will be rapidly replaced by vast neural networks - with all knowledge compressed into their artificial neurons. Unlike organic life, machine intelligence, built within silicon, needs protocols to coordinate and grow. And, like nature, these protocols should be open, permissionless, and neutral. Starting with compute hardware, the Gensyn protocol networks together the core resources required for machine intelligence to flourish alongside human intelligence.
The Role
- Design and implement highly decentralised training pipelines. Scope can span proof of concept development for novel ML research—e.g., our RL-Swarm reinforcement learning framework or Verde verification system—to the maintenance of highly fault-tolerant production systems
Responsibilities
- Build scalable, distributed ML compute systems over uniquely decentralised and heterogeneous infrastructure
- Design and develop novel machine learning algorithms and deep learning applications, and systems for Gensyn