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Seed Global Data is a team focused on producing international data for LLMs. For the training of large models, data is the lifeline of model quality — and the Global Data team is working closely with technical, product, and operations teams to ensure effective data production strategies and execution management.

As a key member of our LLM Global Data Team, the LLM Training Operations Analyst will play a pivotal role in managing the intricate processes involved in training large language models (LLMs) with diverse coding datasets. This role focuses on overseeing and improving operational workflows, primarily for code-related projects, ensuring they are delivered with high quality and efficiency.

• Cooperate with technical teams to locate the potential gaps and conduct relevant mitigations for safety alignment, including but not limited to SFT/RL training.
• Collaborate with the evaluation team to understand the impact of safety alignment trainings; Iterate the evaluation framework to better fit actual scenarios.
• Develop methodologies for data production and acquisition; Ensure high data quality while maximizing the effectiveness and efficiency of data pipelines.

Please note that this role may involve exposure to potentially harmful or sensitive content, either as a core function, through ad hoc project participation, or via escalated cases. This may include, but is not limited to, text, images, or videos depicting:

• Hate speech or harassment
• Self-harm or suicide-related content
• Violence or cruelty
• Child safety

Support resources and resilience training will be provided to support employee well‑being.

• Solid understanding of AI agent safety challenges, such as in AI Search and tool use scenarios.
• 3+ years of experience as a product manager or product strategist.
• Proficiency in English (spoken and written).

• With a strong interest in both LLMs and human behavior/experience/wellbeing. Must be an enthusiastic learner. This position is not suitable for individuals who find reading papers and books to be tedious.
• Collaborative team players who know how to assertively advocate for their ideas without being overbearing. Skilled in maintaining attention to detail while staying focused on prioritized goals and the bigger picture.
• Equipped with a computer science background or coding skills.