Senior Backend Engineer for RL Environments - Remote Contract
Overview
Senior Backend Engineer, contracting 20 hours per week, remote work for micro1. You’ll join a high‑level project to build and test Reinforcement Learning Environments used for AI model training and evaluation. Your backend and DevOps expertise will shape how models learn, reason, and perform under realistic cloud conditions. Prior AI experience isn’t required; deep domain knowledge in distributed systems matters most. The work centers on creating scalable, reproducible environments with deterministic tests and clear documentation, covering production‑grade cloud infrastructure, security, and recoverability. In short, you’ll craft complex testbeds that push AI systems to their limits using real‑world infrastructure patterns, with an emphasis on reproducibility and reliability.
What You'll Do7
- 1Design and implement cloud‑based scenarios that evaluate model skills in deployment, troubleshooting, and design under realistic conditions.
- 2Develop detailed, reproducible test environments covering distributed systems, networking, IAM, message queues, durable storage, observability, rolling deployments, and disaster recovery.
- 3Create deterministic validation tests and golden references to verify environment fidelity and model behavior.
- 4Produce defective variants and failure scenarios to assess model resilience and recovery strategies.
- 5Document architecture, edge cases, and operational workflows to ensure future reuse and clarity.
- 6Collaborate with technical leads to refine environment specs and acceptance criteria through iterative reviews.
- 7Apply DevOps practices and automation to deliver scalable, secure, and maintainable cloud evaluation solutions.
Requirements4
- 1Proven backend development experience in one or more of C++, Python, Rust, Go, Java, or JavaScript.
- 2Solid background in DevOps, cloud infrastructure, CI/CD workflows, and automation tooling.
- 3Ability to design, scale, and secure distributed systems in production settings.
- 4Strong grasp of networking, IAM, queues, durable storage, observability, and disaster recovery concepts.
Who Should Apply
The ideal candidate brings deep backend and DevOps expertise and can translate complex infrastructure needs into testable RL environments. This role suits someone comfortable with cloud patterns, distributed systems, and reproducible research setups. It is less suitable for applicants lacking hands‑on backend or cloud experience, or those who expect AI familiarity as a prerequisite. Common fit gaps include limited exposure to distributed systems design or inadequate experience with CI/CD and security practices, and difficulty producing repeatable, documented environments.
Salary Insight
Compensation is task‑based; pay is tied to completed work that meets project specs. Time to complete tasks varies with experience and workflow. Minimum weekly submission requirements apply; pay is issued per finished task.
Location
Required Skills
Application Tip
Highlight concrete backend and DevOps achievements, especially if you’ve built or tested distributed systems, implemented CI/CD pipelines, or produced reproducible test environments with clear validation criteria.
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1Application received
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