This is a rare point-in-time opportunity: to work on one of the world’s most important technology problems while upending the established political and corporate interests that control and price gouge it. Gensyn will allow machine learning engineers and researchers to train models at a higher scale, and lower cost, than AWS; achieved via a highly specialised deep learning compute protocol with minimal verification overhead (read more in our Lite Paper).
<aside> 🛠 Written in Rust and Python: a trustless protocol that rolls up work from off-chain ML runtimes into a Substrate blockchain for decentralised consensus
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<aside> 🧭 Autonomous environment: fully remote, flat heirarchy, low/no rules: just pure focus on delivering the compute protocol that will push the frontiers of artificial intelligence
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<aside> 💰 Backed by leading crypto infrastructure and deep learning investors, including: Eden Block, Galaxy Digital, Maven 11, CoinFund, Hypersphere, Zee Prime, PEER, Entrepreneur First, Counterview Capital, 7percent, and id4; as well as angels from DeepMind, Livepeer, Pocket, Centrifuge, The University of Cambridge, Twitter, Google, Parity Technologies, and more
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👉 Architect the distributed ML design - design, test, build, and iterate on novel distributed machine learning methods (e.g. Distributed SGD and Decentralised Mixture of Experts)
👉 Build the offchain runtime - implement the distributed ML methods in production for use by ML researchers and engineers globally
👉 Build the ML SDK - wrap ONNX, PyTorch, Tensorflow, Keras, and other frameworks in intuitive ways for minimal friction when training over the Gensyn network
👉 Publish - co-author technical reports/papers describing the system and discuss with the community
✅ Extensive ML + DL research experience - PhD or equivalent level of depth with open source or available examples (papers, code, etc..)
✅ Experience with distributed model development - have previously trained models using data and model parallelism over distributed (ideally highly distributed) hardware
✅ Passion for decentralisation - an understanding of web3 technologies and decentralised principles
✅ Python experience - history of building production-level models and systems in Python
🔥 Publications in distributed ML/DL
🔥 Rust experience
🔥 Some knowledge of protocol engineering