Machine Learning Jobs in Web3

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.