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About Affine

Affine is building an incentivized reinforcement learning (RL) environment that pays miners for measurable model improvements on complex tasks like program synthesis and code generation.

Operating on Bittensor’s Subnet 120, Affine has engineered a sybil-proof, decoy-proof, copy-proof, and overfitting-proof mechanism that rewards genuine advancements in model performance.

Our vision is to commoditize reasoning—the highest form of intelligence—by coordinating a large, permissionless network of contributors working on RL tasks to push the boundaries of what open, distributed AI can achieve.

The Role

Affine’s global RL ecosystem demands infrastructure that is robust, scalable, and fault-tolerant. As a Senior Software Engineer / Architect, you’ll be responsible for designing and implementing the distributed systems that power model evaluation, versioning, leaderboards, and validator mechanisms across Bittensor Subnet-120.

This role is both strategic and deeply technical—you’ll translate research and incentive models into production-ready systems capable of handling 1,000+ model submissions per day with high performance and reliability.

You’ll architect solutions for distributed inference, Pareto frontier computation, load balancing, and real-time observability. Your work will directly shape how Affine’s decentralized infrastructure supports a growing global network of contributors while maintaining fairness, resilience, and speed.

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 recovery strategies to ensure reliability and performance under heavy load.

  • Translate ML and incentive design research into production-grade, scalable systems.

  • Build robust monitoring, logging, and observability tools to track system health and fairness across the network.

  • Contribute to decentralized architecture decisions that enable large-scale, global participation.

Requirements & Qualifications

  • Proven experience in systems engineering, distributed systems, or decentralized infrastructure design.

  • Strong proficiency in Python; Rust experience is a significant plus (especially for protocol-level development).

  • Solid understanding of DevOps and SRE practices, including containerization (Docker), orchestration (Kubernetes), and CI/CD.

  • Demonstrated ability to design and optimize fault-tolerant systems handling high-throughput, low-latency operations.

  • Experience working with real-time, event-driven systems and managing concurrency at scale.

  • Familiarity with monitoring, logging, and observability frameworks for live distributed environments (e.g., Prometheus, Grafana, OpenTelemetry).

Why Affine

  • Build core infrastructure for one of the most advanced decentralized RL environments in the world.

  • Collaborate with leading researchers and engineers in machine learning, incentive design, and decentralized systems.

  • Operate at the intersection of crypto, AI, and open-source innovation.

  • Join an ambitious, high-trust team pushing the limits of distributed intelligence.

Overview

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