ML Engineer - Real-Time Recommendations for E-Commerce

TikTok USDS Joint Venture; Seattle (WA); On-site; USD 130,000 - 246,000; Full time

Job summary

TikTok USDS Joint Venture LLC seeks a skilled ML engineer to build large-scale recommendation models for creators and merchants, using real-time data to boost conversions and monetization. The role emphasizes collaboration with cross-functional teams and impactful ML delivery.

You will work with algorithms such as collaborative filtering, matrix factorization, and deep neural networks, applying Python/C++ and ML tools like TensorFlow or PyTorch to deliver scalable results.

Qualifications

• Bachelor's degree in CS or related field.
• Strong programming and problem-solving ability.
• Open to graduates in applied ML with familiarity in algorithms (e.g., CF, MF, Factorization Machines, Word2vec, LR, GBR, DNN, Wide&Deep, LTR, DIN).
• Experience with Deep Learning tools such as TensorFlow/PyTorch.
• Experience with at least one language like C++ or Python.

Responsibilities

• Build and design large-scale machine learning algorithms to model real-time interests of creators to improve conversion efficiency.
• Optimize TikTok's commodity relationship mining, ranking and recall of product recommendations to boost GMV.
• Analyze large-scale data to build targeted algorithm strategies to empower creators and merchants.
• Support rapid development of TikTok's e-commerce business and serve millions of merchants.

Skills

Strong programming

Problem solving

C++/Python

Applied ML

ML algorithms exposure

Education

Bachelor's degree in CS or related fields

Tools

TensorFlow

PyTorch

Job description

TikTok USDS Joint Venture LLC seeks a skilled ML engineer to build large-scale recommendation models for creators and merchants, using real-time data to boost conversions and monetization. The role emphasizes collaboration with cross-functional teams and impactful ML delivery.

You will work with algorithms such as collaborative filtering, matrix factorization, and deep neural networks, applying Python/C++ and ML tools like TensorFlow or PyTorch to deliver scalable results.