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# Machine Learning Engineer - Agentic Ai (Remote | $85/Hr)

- **Company:** Synthires
- **Location:** Madrid, Spain
- **Salary:** €176,800.0
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Cloud Computing, Software Quality, Code Review, Computer Programming, Continuous Integration, Machine Learning, Tensorflow, Large Language Models, Generative AI, Kubernetes, Machine Learning Operations, Virtual Agents, Docker
- **Published:** August 19, 2026
- **Apply:** https://www.buscojobs.com.es/machine-learning-engineer-agentic-ai-remote-85-hr-en-madrid-ID-368385970

## About the Role

2+ years of professional Machine Learning Engineering experience.
Experience buildingproduction machine learning systems, model deployment infrastructure, LLM applications, or AI-powered products .
Regular experience using AI coding tools such asCursor, Claude Code, Codex, Windsurf, Gemini CLI , or similar coding agents.
Strong understanding ofmachine learning workflows, model deployment, inference systems, and MLOps .
Ability to evaluate AI-generated machine learning implementations and engineering tradeoffs.
Strong programming skills inPythonand modern machine learning frameworks.
Excellent analytical, problem-solving, and written communication skills.
Preferred Qualifications
Experience deploying machine learning systems into production environments.
Experience withPyTorch, TensorFlow, JAX , or similar ML frameworks.
Experience building or evaluatingLLM applications, AI agents, or generative AI systems .
Familiarity with cloud platforms, CI/CD pipelines, Docker, Kubernetes, or distributed ML infrastructure.
Prior experience with AI model evaluation or code review projects.

## Description

ML Engineer (Coding Agent Experience)Position:ML Engineer (Coding Agent Experience)Type:Hourly Contract (Part-Time)Compensation:$85/hourAbout the OpportunityThis opportunity is for experiencedMachine Learning Engineersinterested in contributing to advanced AI research and evaluation projects focused on frontier AI coding models.The role involves evaluating AI-generated machine learning implementations, assessing engineering quality, and applying real-world ML expertise to improve the performance of next-generation AI coding agents.ResponsibilitiesUse frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.Review AI-generated implementations involvingmodel training, inference systems, MLOps, and LLM applications .Identify bugs, edge cases, performance bottlenecks, and implementation failures.Compare outputs from multiple AI coding models and evaluate their technical strengths and weaknesses.Apply professional engineering judgment to realistic machine learning engineering workflows.Provide structured technical feedback to improve AI-generated code quality and model performance.Collaborate with technical reviewers to maintain consistent evaluation standards.Required Qualifications2+ years of professional Machine Learning Engineering experience.Experience buildingproduction machine learning systems, model deployment infrastructure, LLM applications, or AI-powered products .Regular experience using AI coding tools such asCursor, Claude Code, Codex, Windsurf, Gemini CLI , or similar coding agents.Strong understanding ofmachine learning workflows, model deployment, inference systems, and MLOps .Ability to evaluate AI-generated machine learning implementations and engineering tradeoffs.Strong programming skills inPythonand modern machine learning frameworks.Excellent analytical, problem-solving, and written communication skills.Preferred QualificationsExperience deploying machine learning systems into production environments.Experience withPyTorch, TensorFlow, JAX , or similar ML frameworks.Experience building or evaluatingLLM applications, AI agents, or generative AI systems .Familiarity with cloud platforms, CI/CD pipelines, Docker, Kubernetes, or distributed ML infrastructure.Prior experience with AI model evaluation or code review projects.CompensationCompetitive compensation of $85/hour.Weekly payments.Independent contractor engagement.Application ProcessEasy Apply on LinkedInCheck Email for Next StepsParticipate in Resume Evaluation & Interview Stage


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