Senior ML Engineer – Large-Scale Recommender Systems

TikTok USDS Joint Venture; Seattle (WA); On-site; USD 178,000 - 342,000; Full time

Job summary

TikTok USDS Joint Venture in Seattle is seeking engineers to advance large-scale recommendation systems for a variety of feeds, including commodity, live stream, and short video recommendations. You will build and optimize models and data pipelines at scale.

You will develop long- and short-term user interest models, perform feature engineering, and iterate on predictive models for ranking with real-time data processing.

Qualifications

• Bachelor's degree in Computer Science or related field.
• Strong programming and problem-solving ability.
• Experience in applied machine learning, familiar with one or more algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks.

Responsibilities

• Participate in building large-scale recommendation algorithms and systems (10M–100M users).
• Build user interest models and extract information from large data to explore latent interests.
• Design, develop, and iterate predictive models for candidate generation and ranking (CTR/CRP), including real-time pipelines and feature engineering.
• Design and build supporting/debugging tools as needed.

Skills

Programming

Applied ML experience

Deep Learning (TF/PyTorch)

C++/Python

Education

Bachelor's degree in CS or related

Tools

TensorFlow

PyTorch

Large-scale data pipelines

Job description

TikTok USDS Joint Venture in Seattle is seeking engineers to advance large-scale recommendation systems for a variety of feeds, including commodity, live stream, and short video recommendations. You will build and optimize models and data pipelines at scale.

You will develop long- and short-term user interest models, perform feature engineering, and iterate on predictive models for ranking with real-time data processing.