affine-io~1d ago
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Protocol Engineer — Incentive Design / Validation Mechanisms / RL / ML
Remotemid
OtherProtocol Engineer
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Quick Summary
Overview
About Affine Affine is building an incentivized RL environment that pays miners for incremental improvements on tasks like program synthesis and coding.
Technical Tools
pythonrustdistributed-systemsmachine-learning
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. ImpactThis 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.
Location & Eligibility
Where is the job
Worldwide
Fully remote, anywhere in the world
Who can apply
Same as job location
Listing Details
- First seen
- May 5, 2026
- Last seen
- May 7, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 44%
- Scored at
- May 6, 2026
Signal breakdown
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External application · ~5 min on affine-io's site
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