ML Engineer, Large-Scale Recommendation Systems

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 123,000 - 259,000; Full time

Benefits offered by this job

Medical insurance

401(k) with match

Paid parental leave

Paid time off and holidays

Job summary

TikTok USDS Joint Venture is seeking machine learning engineers to advance large-scale recommendation systems for TikTok’s feed and e-commerce experiences. You will work on candidate generation, ranking, and live data pipelines within a fast-paced, cross-functional team.

We look for strong programming skills, solid knowledge of deep learning frameworks, and hands-on experience with scalable ML methods. This is an in-person role with collaboration across diverse teams and a focus on real-world

Qualifications

• Bachelor's degree in Computer Science or related field.
• Strong programming and problem-solving ability.
• Experience with algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep.
• Experience with Deep Learning Tools such as TensorFlow or PyTorch.
• Experience with C++ or Python or equivalent.

Responsibilities

• Build large-scale recommendation algorithms and systems (10M–100M users).
• Develop long and short-term user interest models and extract insights from large data.
• Design, develop, evaluate and iterate predictive models for candidate generation and ranking, including real-time data pipelines and feature engineering.
• Design and build supporting/debugging tools as needed.

Skills

Programming

Problem solving

ML algorithms

Deep learning tools

C++/Python

Education

Bachelor's degree in CS or related

Tools

TensorFlow

PyTorch

Job description

TikTok USDS Joint Venture is seeking machine learning engineers to advance large-scale recommendation systems for TikTok’s feed and e-commerce experiences. You will work on candidate generation, ranking, and live data pipelines within a fast-paced, cross-functional team.

We look for strong programming skills, solid knowledge of deep learning frameworks, and hands-on experience with scalable ML methods. This is an in-person role with collaboration across diverse teams and a focus on real-world