Data Operations Project Intern (AI Data & Safety) - 2026 Start (BS/MS) Global Operations Projec[...]

ByteDance; Singapore; On-site; SGD 40,000 - 60,000; Full time

Job summary

ByteDance is hiring an International Data Operations Project Intern for the AI Data & Safety team in Singapore. This role includes responsibilities such as supporting model evaluation, managing projects, developing tools, and ensuring quality in data annotation across various domains. A Bachelor's degree in a related field, experience in project management, and proficiency in both English and Mandarin are required. A passion for AI and strong analytical skills are essential for success. Join ByteDance to drive innovation in AI data operations.

Qualifications

• Bachelor's degree in a related technical field or equivalent practical experience.
• Experienced in project or operations management roles.
• Ability to create tools or solutions with code scripts.
• Strong independent problem-solving skills.
• Deep interest in LLMs and adaptability to fast-paced environments.
• Proficient in English and Mandarin.

Responsibilities

• Support model evaluation and user-growth projects.
• Maintain strong relationships with stakeholders and manage updates.
• Develop code-based tools for project purposes.
• Support annotation operations across multiple data domains.
• Analyze annotation quality and model performance using statistical methods.

Skills

Project management

Data analysis

Problem-solving

Programming (Python, SQL)

Bilingual (English, Mandarin)

Education

Bachelor's degree in Computer Science/Data Science/Artificial Intelligence

Tools

Python

SQL

HTML

LaTeX

Markdown

Job description

International Data Operations Project Intern (AI Data & Safety) - 2026 Start (BS/MS)

The AI Data and Safety team plays a critical role in advancing Seed's foundational models, AI products across modalities, and improving AI-native applications built on the Seed model series. We work across the data lifecycle, from defining evaluation approaches, 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 and multilingual 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 internal 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 more large AI models are being developed, high‑quality data has become the core fuel driving the leap in model capabilities. Our team – AI Data & Safety – Data Annotation and Evaluation Operations – is the builder and operator of this critical link. Our value lies in transforming the “intelligence” scattered across individual experience and organizational knowledge into “data” that models can understand and learn from by establishing a scientific and efficient data production and operation system. This directly drives the iteration of model capabilities and the implementation of various AI applications. We serve not only as key infrastructure supporting ByteDance’s AI strategy, but also as the core bridge connecting human wisdom and machine intelligence.

Responsibilities

1. Support model evaluation, training, and user-growth related projects, ensuring that objectives and quality standards are achieved in time. Identify risks and propose corrective actions as required to keep projects on track.
2. Establish and maintain strong relationships with product managers, project owners, researchers, and other external collaborators. Communicate project updates and bottlenecks in a timely fashion to ensure prompt follow‑up by project owners or project managers.
3. Develop code‑based tools for diverse project‑related purposes, such as automating key processes, conducting data analysis, and converting file types and formatting to meet the specific requirements of various platforms.
4. Support general annotation operation improvement initiatives across multiple data domains such as Reasoning, General Knowledge, STEM, and Humanities. Create and maintain technical guidelines and casebooks to support consistent and high‑quality data production from external parties.
5. Analyze annotation quality, model performance, and dataset coverage through statistical, visual, and programmatic methods. Employ tools like Python (Pandas, NumPy, Matplotlib) and SQL to generate actionable insights, monitor the health of the data pipeline, and support model training operations. Collaborate with model trainers and researchers to inform training strategies and guide data‑centric iterative improvements.

Qualifications

Minimum Qualifications

1. Bachelor's degree in Computer Science/Data Science/Artificial Intelligence, a related technical field, or equivalent practical experience.
2. Experienced in project or operations management roles on software engineering teams, possessing strong project management skills to design, manage, and proactively optimize complex workflows, while balancing independent judgment with collaborative teamwork in a fast–paced, project‑based environment.
3. Experienced in creating tools or solutions with code scripts.
4. Independent problem‑solving skills with the ability to understand and communicate technical concepts effectively to the layman.
5. Deep interest in LLMs, computational thinking, and ability to adapt to a rapidly changing, high‑intensity work environment with an objective‑driven mindset.
6. Familiar and able to work with markup and typesetting languages: HTML, LaTeX and Markdown.
7. Exceptional proficiency in both English and Mandarin, with strong written and oral communication skills required to collaborate with internal teams and stakeholders across English and Mandarin‑speaking regions.

Preferred Qualifications

1. Experience in model annotation and evaluation processes, working with leading AI/LLM companies on technical projects.
2. Experience with codebases and understanding of software development processes, coding best practices, and version control systems (e.g., Git). Familiarity with full‑stack concepts, including front‑end interfaces, back‑end logic, and database integration.
3. Enthusiasm for learning, engaging with diverse technical case studies, working with global teams, and comfort with using and developing simple technology tools that enhance project efficiency.