Responsibilities

The AI Data and Safety team plays a critical role in advancing Seed foundational models across modalities and improving AI-native applications built on the Seed model series. We work across the data lifecycle, from defining evaluation approaches and translating user feedback and benchmark outcomes into data requests, to building scalable processes that improve data quality and support rapid model iteration. Our team combines technical and operational capabilities, bringing together multidisciplinary talent across product management, data engineering, and data operations. Our work is driven by people who think deeply about model behavior, move quickly to solve complex problems, and bring first-hand experience as both builders and users of models and agents. In close partnership with Seed researchers, industry experts, and leading data vendors, we tackle challenging data problems at the frontier of AI development, helping improve both model performance and user experience. As a project intern, you will have the opportunity to engage in impactful short-term projects that provide you with a glimpse of professional real-world experience. You will gain practical skills through on-the-job learning in a fast-paced work environment and develop a deeper understanding of your career interests. Applications will be reviewed on a rolling basis - we encourage you to apply early. The AI Data & Safety team is the backbone of our Seed Foundation Models and AI-native applications. We provide end-to-end multi-modal data services, covering everything from establishing evaluation standards and large-scale data production to building "data flywheels." In this role, you will sit at the intersection of product management, data engineering, and research. You won’t just be managing tasks; you’ll be a front-line contributor to model breakthroughs, working alongside world-class researchers and global data vendors to solve the most complex data challenges in the AI frontier. As an intern, you will support the PM lead in orchestrating the engine that powers our LLMs and VLMs. Your focus will be split between operational excellence and technical innovation. 1. Direct Impact: Your data directly dictates how our foundation models behave. 2. High-Growth Environment: Work in a vibrant AI ecosystem with a global team of experts from diverse backgrounds. 3. Technical Exposure: Gain hands-on experience in how industrial-grade AI is actually built, from raw data to fine-tuned models. Key Responsibilities 1. Model Analysis & Feedback: Deep-dive into model training goals. Analyze user behavior and "Bad Cases" to pinpoint model weaknesses and suggest actionable data-driven improvements. 2. Data Strategy & Sourcing: Assist in defining data construction strategies (including synthetic data). Keep a pulse on global market trends to ensure our datasets remain competitive. 3. Vendor & Project Management: Manage progress with global data labeling vendors. You will be responsible for defining task specs, monitoring throughput, and ensuring high-quality delivery under tight deadlines. 4. Pipeline Automation: Leverage LLMs to build automated data production and quality check (QC) systems. You’ll help design the logic that allows us to scale data production without sacrificing quality. 5. Cross-Border Collaboration: Act as a bridge between our CN-based research team and overseas vendors to ensure seamless communication and alignment on data standards.

Qualifications

Minimum Qualifications 1. Academic Background: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related technical field. 2. Technical Toolkit: Proficient in Python (e.g., Pandas, NumPy) for data manipulation and automation, with experience in prompt engineering to design complex prompts for LLMs to generate and evaluate synthetic data. 3. AI Fluency: A solid understanding of LLM/VLM architectures. You should be an active user of AI tools and stay updated on the latest research papers and product releases. 4. Analytical Mindset: You enjoy digging through massive datasets to find patterns. You can translate a "vague model error" into a "concrete data requirement." 5. System Thinking: Ability to design complex workflows and rules for data processing and evaluation. 6. Communication: Fluent in English and Mandarin to collaborate with international teams and vendors based in Chinese-speaking markets. Proficiency in Mandarin is required for reviewing technical documents. 7. Grit: You are hardworking, detail-oriented, and take extreme ownership of data quality. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://jobs.bytedance.com/en/legal/privacy If you have any questions, please reach out to us at apac-earlycareers@bytedance.com

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