Rust 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 incentivized RL environment requires high-performance, fault-tolerant systems that can scale with global participation. As a Senior Software Engineer / Architect, you’ll design and build the core infrastructure powering distributed evaluation, model versioning, real-time leaderboards, and validation mechanisms across Affine, Bittensor’s subnet-120.

This role emphasizes systems architecture at scale: distributed inference pipelines, Pareto frontier computation, caching and load-balancing strategies, and resilient validation frameworks. You’ll take the protocols and research outputs from our ML and incentive teams and engineer them into production-grade, decentralized infrastructure capable of handling 1,000+ model submissions per day.

We’re seeking someone who thrives on complex engineering challenges—from scaling throughput and latency-sensitive evaluation, to building monitoring systems that track the health of a live, competitive network. Your work ensures Affine’s infrastructure can handle the demands of global participation while remaining secure, fair, and performant.

Responsibilities

• Architect and implement distributed systems for model evaluation, inference pipelines, and versioning.
  
  
  
• Design high-availability infrastructure for real-time leaderboards and validator mechanisms.
  
  
  
• Develop caching, load balancing, and failure recovery strategies to ensure performance and resilience.
  
  
  
• Translate research protocols into production-grade systems, collaborating closely with ML and incentive design teams.
  
  
  
• Build monitoring and observability tools to track system health, throughput, and fairness across the subnet.
  
  
  
• Contribute to architectural decisions for decentralized systems supporting large-scale participation.
  
  
  

Qualifications

• Strong experience in systems engineering, distributed/decentralized systems, and scalable networking.
  
  
  
• Proficiency in Python; exposure to Rust a strong plus, particularly for protocol-level engineering.
  
  
  
• Background in DevOps practices, including containerization, orchestration, and CI/CD pipelines.
  
  
  
• Demonstrated ability to design and optimize high-performance, fault-tolerant infrastructure.
  
  
  
• Experience with latency-sensitive and throughput-intensive systems at scale.
  
  
  
• Familiarity with monitoring, logging, and observability frameworks for live distributed environments.