> Markdown version of [/jobs/ext/2728030-applied-scientist-tiktok-e-commerce-recommendation](https://www.wearedevelopers.com/jobs/ext/2728030-applied-scientist-tiktok-e-commerce-recommendation). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Applied Scientist- TikTok E-Commerce Recommendation

- **Company:** Tiktok Shop
- **Location:** Seattle, WA, United States
- **Experience:** Experienced
- **Salary:** $153,900.0 - $300,960.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Program Optimization, Software Debugging, Information Retrieval, Machine Learning, Natural Language Processing, Tensorflow, Feature Engineering, Pytorch, Deep Learning, Build Management, Information Technology, Data Pipelines
- **Published:** September 5, 2026
- **Apply:** https://www.themuse.com/jobs/tiktok/applied-scientist-tiktok-ecommerce-recommendation

## About the Role

* MS/PhD in Computer Science, related technical field or equivalent industrial research experience.
 * 3+ years of working experience in one of the following fields: recommendation algorithm, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.
Preferred Qualifications:

 * Familiar with at least one of the mainstream deep learning frameworks, like TensorFlow or PyTorch.
 * Passionate about solving complex and challenging problems

## Description

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. We are a group of applied machine learning engineers and data scientists that focus on E-commerce recommendations. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested and excited in applying large scale machine learning to solve various real-world problems in E-commerce., * Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok.

 * Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
 * Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.
 * Design and build supporting/debugging tools as needed.


## Related Videos

- [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology)
- [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs)
- [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale)
- [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery)

## Related Articles

- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
- [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)
- [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this)
- [Top Tech YouTube Channels for Developers in 2023](https://www.wearedevelopers.com/magazine/261-top-tech-youtube-channels-for-developers-in-2023)
- [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)
- [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)