SWE Infrastructure Specialist (JS/TS/Python) – Freelance AI Trainer
New
J
JobgetherArtificial Intelligence
IndiaContract
Salary80 - 150 USD per hour
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Job Details
- Required Skills
- PythonJavascriptSoftware ArchitectureTypeScriptDevOpsDistributed Systems
Requirements
- Bachelor’s, Master’s, or PhD degree in Computer Science, Software Engineering, or a related technical field preferred.
- Strong proficiency in JavaScript, TypeScript, and Python.
- Professional experience in software engineering, infrastructure engineering, platform engineering, DevOps, cloud architecture, performance engineering, or quality engineering.
- Strong understanding of distributed systems, software architecture, scalability, reliability, and system performance.
- Experience with cloud platforms, deployment workflows, and Infrastructure-as-Code concepts.
- Ability to analyze technical tradeoffs and evaluate architectural decisions.
- Familiarity with testing strategies, debugging methodologies, monitoring, and production reliability practices.
- Strong problem-solving skills and systems-level thinking.
- Ability to clearly document technical reasoning and communicate complex concepts effectively.
- Self-directed work style with the ability to manage independent technical tasks in a remote environment.
Responsibilities
- Engage with AI models on advanced infrastructure and platform engineering challenges using JavaScript, TypeScript, and Python.
- Evaluate model responses for architectural soundness, technical accuracy, logical reasoning, and practical feasibility.
- Analyze software and infrastructure designs involving cloud systems, distributed architectures, deployment workflows, and scalability challenges.
- Assess code quality, testing strategies, reliability considerations, and engineering best practices.
- Identify performance bottlenecks, deployment risks, failure scenarios, and opportunities for system improvement.
- Review infrastructure decisions involving Infrastructure-as-Code, environment isolation, state management, and operational reliability.
- Create reproducible failure cases and provide structured feedback to improve AI model performance.
- Contribute insights into prompt design, evaluation methodologies, and quality benchmarks.
- Communicate complex technical concepts clearly, explaining architectural tradeoffs and system-level reasoning.
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