Non Tech Web3 Jobs in Remote, Remote
3,366 jobs found
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Job Position | Company | Posted | Location | Salary | Tags |
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Affine.io | Remote | $140k - $250k | |||
Affine.io | Remote | $18k - $42k | |||
Hype Partners Ltd. | Remote | $86k - $180k | |||
Bondex | Remote |
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Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Gnosis Guild | Remote |
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Status | Remote | $58k - $90k | |||
Oasisnetwork | Remote | $36k - $65k | |||
Base | Remote | $90k - $100k | |||
Ethereum Foundation | Remote |
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Yieldschool | Remote | $100k - $240k | |||
Seimus | Remote |
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ZIGCHAIN | Remote |
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OpenZeppelin | Remote | $105k - $180k | |||
Metis.io | Remote | $10k | |||
Ethereum Foundation | Remote |
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About Affine
Affine is building an incentivized RL environment that pays miners for incremental improvements on tasks like program synthesis and coding. Operating on Bittensor's Subnet 120, we’ve created a sybil-proof, decoy-proof, copy-proof, and overfitting-proof mechanism that rewards genuine model improvements. Our vision is to commoditize reasoning—the highest form of intelligence—by directing and aggregating the work of a large, non-permissioned group on RL tasks to break the intelligence sound barrier.
Overview
Affine’s competitive RL network depends on robust, incentive-aligned protocols that cannot be gamed. As a Protocol Engineer, you’ll design and implement the cryptographic, validation, and anti-sybil mechanisms that make our reward system trustworthy and tamper-resistant.
Your focus will be on building the rules of the game: incentive structures that drive genuine model improvement, and validation systems that fairly identify dominating models on the pareto frontier.
Responsibilities
- Design and implement incentive mechanisms that reward genuine model improvement.
- Build validation systems to detect and prevent gaming strategies, including sybil attacks, copy detection, decoy models, and overfitting.
- Anticipate adversarial strategies and harden protocol rules against potential exploits.
- Collaborate with researchers and ML engineers to encode anti-gaming defenses into the protocol itself.
- Develop incentive loops and validation frameworks that scale with increasing participation while maintaining fairness and decentralization.
Qualifications
- Strong background in distributed systems, cryptography, or blockchain protocols.
- Experience with incentive design, mechanism design, or adversarial machine learning.
- Proficiency in Python and/or Rust, with an emphasis on system-level engineering.
- Familiarity with reinforcement learning (RL) concepts and validation frameworks.
- Mindset oriented toward adversarial thinking: anticipating attack vectors and designing defenses.
- Experience in decentralized or open-network environments is a plus.
Impact
This role is ideal for engineers who think in terms of systems and adversaries. By ensuring Affine’s RL competitions remain fair, decentralized, and self-reinforcing, your work will directly enable the network to continuously push AI capability forward.