Gensyn is building infrastructure to coordinate machine learning compute across a decentralized network. The tech stack (PyTorch, JAX, TensorFlow, Go, Rust, Ethereum) reveals a heavy focus on both ML frameworks and blockchain-backed coordination — they're adopting verification and composability as first-class concerns in distributed training. Active projects span neural network verification, peer-to-peer reinforcement learning, and scalable deep learning systems, with engineering and research roles making up the majority of their 11–50-person team.
Tech Stack 18 technologies
Core StackPyTorch TensorFlow TypeScript JavaScript Go Python Rust Cursor GitHub Copilot Kubernetes Terraform JAX HTML CSS Codex Claude Ethereum Ethereum Virtual Machine
What Gensyn Is Building
◆Challenges
- Developer workflow integration pain points
- Complex deliverables under tight deadlines
- Scaling distributed systems
- High-load infrastructure
- Hiring and retaining world class talent
▲Active Projects
- Scalable distributed machine learning research
- Decentralized neural network verification
- Consumer ai applications powered by gensyn network
- Architecture and tech stack for products built on gensyn’s decentralised ai network
- Web applications for gensyn users and community members
- Sdks, apis, and developer infrastructure roadmap
- Massive scale deep learning systems focusing on modularity, composability, verifiability, and continual learning
- Experimental frameworks and test benchmarks for ml research in high-scale decentralised settings
- Distributed training pipelines
- Peer-to-peer reinforcement learning
Hiring Activity
Steady9 roles · 3 in 30d
Department
Seniority
Notable leadership hires: Head of Marketing
Company intelligence
