Knowledge Graph Internship – Knowledge Graph

Job Description

Machine Learning Engineer Intern (E-Commerce Knowledge Graph – CV/Multimodal/NLP) – 2026 Summer (BS/MS) | ByteDance

The Tone:
This is an internship at ByteDance, a global technology company founded in 2012 that inspires creativity and enriches life through a suite of over a dozen popular products like TikTok and CapCut. The Knowledge Graph team is responsible for building the foundational neural network of e-commerce, which is critical for understanding and organizing vast amounts of product, influencer, and merchant data. This role is pivotal in processing complex information to power personalized recommendations and strategic business insights across the platform, bridging various aspects of the business. ByteDance aims to offer students industry exposure and hands-on experience, supporting both personal and professional growth over a 12-week period.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: US-based (various cities)
• Pay: $42.75 hourly
• Team: Knowledge Graph team
• Mission: To build and manage the e-commerce knowledge graph, connecting products, content, buyers, and brands to power recommendations and business insights.
• Tech Stack: Python, Java, C/C++, Spark, PyTorch, TensorFlow, Keras

What You’ll Actually Do
• Graph Crafting: Craft intricate knowledge graphs encompassing product/content insights and category/brand/SPU development.
• Map Architecture: Architect knowledge maps detailing buyer and product connections for the e-commerce platform.
• Entity Categorization: Categorize e-commerce products, influencers, and merchants to build platform understanding and structure.
• Data Mining: Mine product information and provide processed, structured data to internal recommendation teams.
• Competitive Analysis: Conduct competitive research, identifying top-performing items and analyzing market performance trends.

The Must-Haves
• Background: Student completing or recently completed a Bachelor’s or Master’s degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Experience: Ability to commit to a 12-week full-time work period during Summer 2026, with experience in at least one of these technological areas: LLM, natural language generation, named entity recognition, machine translation, question answering, knowledge graph, information extraction, text mining and classification; Computer vision, facial recognition, multimodal learning, object detection & tracking, image classification; or Machine learning, transfer learning, graph embedding, representative learning, large-scale optimization, recommendation, reinforcement learning.
• Skills: Strong coding skills in at least one programming framework (e.g., Python, Java, C/C++, Spark), familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, Keras), and strong analytical and problem-solving abilities.