MLOps Engineer (Remote)

hire feed • Latin America

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Design and evaluate autonomous AI agents across multiple LLMs, shape the future of agentic AI systems, and provide expert human feedback to leading AI organisations. Key responsibilities include AI agent evaluation, technical assessment, and project workflow management. The ideal candidate will have experience in backend engineering, AI automation, and complex systems integration.

Key Highlights

AI Agent Evaluation

Technical Assessment

Project Workflow Management

Key Responsibilities

Write evaluation rubrics with objective pass/fail criteria

Debug agent traces to identify failure patterns

Stress test agents against edge cases, prompt injection, and tool misuse

Assess production-grade modular software architecture

Analyse multi-turn system interactions and behaviours

Provide high-density technical feedback for LLM training

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Technical Skills Required

Python JavaScript Go Java SQL databases

Benefits & Perks

Hourly compensation ranges from USD $30–$50

Weekly payments via supported payout platforms

Equal Opportunity Statement

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Nice to Have

Experience integrating agents with live tools such as Supabase, Gmail, and other APIs

Familiarity with persistent state and session-tracking patterns

Experience identifying privacy leaks, authority escalation, or indirect prompt injection vulnerabilities

Job Description

Job Title: MLOps Engineer (Remote)
Location: Remote (LATAM, Puerto Rico, Argentina, Peru, Colombia, Brazil, Mexico, Chile, Bolivia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Nicaragua, Panama, Paraguay, Trinidad and Tobago, Uruguay, Venezuela))
Work Mode: Fully Remote

Role Overview

Help design and evaluate autonomous AI agents across multiple LLMs, spanning health, education, daily life, and other real-world domains (all coding work). Shape the future of agentic AI systems by providing expert human feedback to leading AI organisations. Help train Large Language Models (LLMs) for complex, multi-step architectural workflows.

Key Responsibilities

AI Agent Evaluation

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