Technical Product Manager
Job Description
Gensyn is a decentralized protocol networking together compute resources for machine learning. This 0-to-1 Technical Product Manager role owns core infrastructure systems — including REE (verifiable execution of AI/ML workloads) and AXL (p2p networking for AI agents) — shaping developer-facing APIs, SDKs, and workflows for the decentralized training protocol.
Responsibilities
- Own product direction and delivery for core infrastructure systems
- Partner with engineering/research to shape distributed systems into usable products
- Define APIs, SDKs, and developer workflows for the protocol
- Engage directly with ML engineers/researchers to identify friction points
- Validate early product-market fit through design partners and use cases
- Track adoption, reliability, and developer-satisfaction metrics
What we are looking for
- Early-stage/high-growth startup product experience
- Distributed systems, compute platforms, or compiler background
- API/SDK or developer-platform product management
- Strong technical communication for translating complex systems
- Python, Go, or Rust (hands-on, nice-to-have)
Additional Information
Gensyn is a decentralized protocol for networking together compute resources for machine learning. This Technical Product Manager role is 0-to-1, owning two specific infrastructure systems: REE (verifiable execution of AI/ML workloads) and AXL (peer-to-peer networking for AI agents). Compensation includes equity plus a token pool.
Perks and Benefits
- Competitive salary and equity/token pool
- Comprehensive health coverage
- Remote-friendly / flexible work
- Learning & development budget
Keywords: Product Management, AI, Distributed Systems, Developer Platform
Gensyn
📍 London, United KingdomVisit Company WebsiteGensyn is a decentralized protocol that networks together compute resources from around the world for machine learning training and other compute-intensive workloads. It uses verification mechanisms to ensure distributed ML computation is performed correctly, aiming to make ML compute a globally accessible, trust-minimized market.
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