RE
Data Generalist
- Hiring from
- Australia
- Work type
- Remote
- Posted
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Discover full-time remote Data Generalist jobs in Sydney for 2026. Join Rex.zone to optimize AI/ML training pipelines through expert data labeling, RLHF, and QA evaluation.
Core Responsibilities in AI/ML Training Pipelines
As a senior remote data generalist, you will handle diverse tasks including RLHF (Reinforcement Learning from Human Feedback), complex data labeling, and comprehensive QA evaluation. Your daily workflows will involve prompt evaluation, named entity recognition, and content safety labeling across NLP and computer vision annotation projects. You will collaborate with annotation vendors and freelance experts to maintain high standards in LLM training pipelines.
Qualifications For Remote Data Generalists
We are looking for mid-senior professionals, though we occasionally offer entry-level and contract opportunities. Candidates must possess deep expertise in large language model evaluation and model performance improvement. You should be comfortable working in a fully remote environment, engaging with cross-functional engineering teams, and ensuring strict annotation guidelines compliance for diverse AI models.
Core Responsibilities in AI/ML Training Pipelines
As a senior remote data generalist, you will handle diverse tasks including RLHF (Reinforcement Learning from Human Feedback), complex data labeling, and comprehensive QA evaluation. Your daily workflows will involve prompt evaluation, named entity recognition, and content safety labeling across NLP and computer vision annotation projects. You will collaborate with annotation vendors and freelance experts to maintain high standards in LLM training pipelines.
Qualifications For Remote Data Generalists
We are looking for mid-senior professionals, though we occasionally offer entry-level and contract opportunities. Candidates must possess deep expertise in large language model evaluation and model performance improvement. You should be comfortable working in a fully remote environment, engaging with cross-functional engineering teams, and ensuring strict annotation guidelines compliance for diverse AI models.
