Machine Learning PhD Intern – E-commerce AI

Job Description

Research Scientist Intern– E-commerce Recommendation(LLM Applications) – Global Frontier Tech Recruitment Program – 2027 Start (PhD) | TikTok

The Tone:
This is a PhD internship at TikTok, a company that operates a leading short-form mobile video platform and is expanding into global e-commerce. This role is crucial for developing the core algorithmic and technical backbone of TikTok’s Global E-commerce business. The intern will focus on applying Large Language Models (LLMs) to enhance recommendation systems, contributing directly to the organization’s future plans in emerging technologies and its mission to deliver personalized shopping experiences and high-quality products to users worldwide.

The TL;DR
• Role: Internship
• Location: Various locations (e.g., Los Angeles)
• Pay: $57 hourly
• Team: The Data–E-commerce team, serving as the core algorithm and technical backbone of the Global E-commerce business.
• Mission: Build a foundational large model tailored for Global E-commerce scenarios, unifying key elements and enabling end-to-end intelligent decision-making.
• Tech Stack: TensorFlow, PyTorch, Hadoop, MapReduce, Spark

What You’ll Actually Do
• Recommendations: Build industry-leading recommendation systems to improve user experience, content ecosystem, and platform security.
• Generative Techniques: Explore generative recommendation techniques, including Diffusion Models, prompt learning, and multimodal content generation, to unlock new capabilities in content discovery.
• Unified Systems: Construct multi-model and cross-scenario systems for unified recommendations across livestreams, short videos, and search within the e-commerce platform.
• ML Solutions: Deliver end-to-end machine learning solutions to address critical product challenges in e-commerce.
• System Ownership: Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.

The Must-Haves
• Background: Currently pursuing a PhD in Computer Science, Computer Engineering, or a related technical discipline. Possess a strong foundation in machine learning and knowledge of cutting-edge AI technologies.
• Experience: Demonstrated experience with big data frameworks like Hadoop, MapReduce, and Spark, along with proficiency in TensorFlow or PyTorch for model training and deployment. Understanding of training acceleration techniques such as mixed precision and distributed training. Publications in top-tier academic conferences or competition experience are preferred.
• Skills: Machine learning, Artificial Intelligence, Big Data frameworks, Deep learning frameworks (TensorFlow, PyTorch), Model training and deployment.
• Bonus: Expertise in model compression and inference acceleration techniques (quantization, pruning, distillation, TensorRT optimization). In-depth research experience in Computer Vision & Multimodality or Natural Language Processing (NLP), particularly with large-scale models and e-commerce applications. Achievements in relevant competitions (e.g., Kaggle, COCO, ImageNet, GLUE) or publications in accredited conferences (e.g., CVPR, ICCV, ACL, EMNLP) are highly valued.