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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 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.