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Job Title: A. I Trainer (LLM & Generative AI Specialist)Location: Remote (Worldwide)Job Summary: We are seeking a detail-oriented and analytical AI Trainer to support the development and improvement of artificial intelligence systems. The AI Trainer will be responsible for training, evaluating, and refining machine learning models by providing high-quality data annotation, feedback, and performance analysis. Responsibilities Architect and manage end-to-end training workflows, including supervised fine-tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and red-teaming exercises. Develop complex prompt templates and testing scenarios to evaluate model performance across various domains (coding, creative writing, reasoning, multilingual tasks). Define and maintain rubrics for model output quality. Conduct in-depth analysis of model failures and edge cases to identify root causes of bias, hallucination, or logical errors. Create high quality “golden datasets” that set the standard for model behavior in your area of expertise. Guide and review the work of junior trainers and data annotators, ensuring consistency and high standards across the global team. Maintain detailed documentation of training methodologies, model behaviors, and iterative improvements for internal stakeholders and research teams. Work closely with Machine Learning Engineers and Product Managers to translate technical research goals into actionable training tasks for human annotators. Identify barriers in the training workflow and propose improvements to the internal platforms or tools used for data annotation and model evaluation. Design and implement strategies for generating high-quality synthetic data to argument training datasets and improve model robustness in niche scenarios. Requirements Minimum of 2 years of experience in a relevant field (e. g., Software Engineering, Computer Science). Proven ability to dissect complex problems, identify patterns in data, and articulate abstract concepts clearly. Familiarity with Python, JSON, or APIs is a plus. A willingness to learn internal tooling and understand basic machine learning concepts is required. Comfortable reading technical papers or documentation to understand how models are expected to behave and staying updated on the latest A. I. safety research. Experience using data analysis or metrics to justify training decisions and measure the success of specific interventions on model performance. Ability to manage multiple concurrent projects, prioritize tasks effectively in a fast-paced environment, and meet tight deadlines. Willingness to shift focus between highly technical tasks (e. g., ranking code) and creative tasks (e. g., writing fiction) as project needs evolve.
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Job Title: A. I Trainer (LLM & Generative AI Specialist)Location: Remote (Worldwide)Job Summary: We are seeking a detail-oriented and analytical AI Trainer to support the development and improvement of artificial intelligence systems. The AI Trainer will be responsible for training, evaluating, and refining machine learning models by providing high-quality data annotation, feedback, and performance analysis. Responsibilities Architect and manage end-to-end training workflows, including supervised fine-tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and red-teaming exercises. Develop complex prompt templates and testing scenarios to evaluate model performance across various domains (coding, creative writing, reasoning, multilingual tasks). Define and maintain rubrics for model output quality. Conduct in-depth analysis of model failures and edge cases to identify root causes of bias, hallucination, or logical errors. Create high quality “golden datasets” that set the standard for model behavior in your area of expertise. Guide and review the work of junior trainers and data annotators, ensuring consistency and high standards across the global team. Maintain detailed documentation of training methodologies, model behaviors, and iterative improvements for internal stakeholders and research teams. Work closely with Machine Learning Engineers and Product Managers to translate technical research goals into actionable training tasks for human annotators. Identify barriers in the training workflow and propose improvements to the internal platforms or tools used for data annotation and model evaluation. Design and implement strategies for generating high-quality synthetic data to argument training datasets and improve model robustness in niche scenarios. Requirements Minimum of 2 years of experience in a relevant field (e. g., Software Engineering, Computer Science). Proven ability to dissect complex problems, identify patterns in data, and articulate abstract concepts clearly. Familiarity with Python, JSON, or APIs is a plus. A willingness to learn internal tooling and understand basic machine learning concepts is required. Comfortable reading technical papers or documentation to understand how models are expected to behave and staying updated on the latest A. I. safety research. Experience using data analysis or metrics to justify training decisions and measure the success of specific interventions on model performance. Ability to manage multiple concurrent projects, prioritize tasks effectively in a fast-paced environment, and meet tight deadlines. Willingness to shift focus between highly technical tasks (e. g., ranking code) and creative tasks (e. g., writing fiction) as project needs evolve.
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Your safety comes first — read before you go
Taf4All only lists job offers published by third parties. We are not the employer, we do not conduct these recruitments, and we cannot guarantee what happens once you make contact — you deal directly with the person or company behind the offer, at your own risk.
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