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Remote AI Generalist

Rex.zoneApplies on LinkedInData & Analytics
Hiring from
Austria, Ireland
Work type
Remote
Posted
Sep 23, 2026
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Explore full-time remote AI generalist jobs in Ireland for 2026. Join Rex.zone to drive large language model evaluation, RLHF, and training data quality for advanced AI pipelines.

About The Remote AI Generalist Role

Are you looking for remote AI generalist jobs in Ireland for 2026? Rex.zone is hiring mid-senior professionals for full-time, freelance, and contract opportunities. In this role, you will directly impact large language model evaluation and model performance improvement. Your daily workflows will encompass RLHF (Reinforcement Learning from Human Feedback), prompt evaluation, and complex data labeling. By ensuring strict annotation guidelines compliance, you will help leading AI labs and tech startups build safer, more accurate NLP and computer vision systems. Whether you are an entry-level specialist or a senior engineer, this remote position offers the chance to shape the future of LLM training pipelines.

Key Responsibilities in AI/ML Training Pipelines

As a Remote AI Generalist, your primary focus is training data quality. You will execute QA evaluation across diverse datasets, performing named entity recognition, content safety labeling, and computer vision annotation. You will evaluate AI-generated responses for factual accuracy, tone, and alignment, providing high-quality human feedback to refine foundational models. Collaborating with remote teams at Rex.zone, you will troubleshoot edge cases in prompt engineering and optimize data annotation workflows for global AI annotation vendors.

Qualifications And Skills

Candidates must possess strong analytical skills and a deep understanding of AI/ML concepts. Experience with RLHF, NLP, and LLM training is highly preferred. You should be comfortable working in a fully remote environment, managing your time effectively across different time zones. A background in linguistics, computer science, or data science is advantageous, along with a proven track record of maintaining high annotation guidelines compliance in previous data labeling projects.

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