Senior Recommender ML Engineer — Scale Systems

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

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) with company match

Parental leave

Disability insurance

Life insurance

Wellbeing benefits

Paid holidays

Paid sick leave

Paid personal time

Job summary

TikTok USDS Joint Venture LLC is hiring applied machine learning engineers and data scientists to work on general feed and e-commerce recommendations. The team develops scalable algorithms to boost user engagement and satisfaction, turning innovative ideas into business-impacting solutions.

You will work on large-scale recommendation systems, design user models, and build end-to-end ML pipelines for candidate generation and ranking, including live data processing and feature engineering.

Qualifications

• Bachelor's degree or higher in Computer Science or related field.
• Strong programming and problem-solving ability.
• Experience in applied machine learning with familiar algorithms (CF, Matrix Factorization, FM, Word2vec, LR, GB Trees, DNNs).
• Experience with Deep Learning tools such as TensorFlow/PyTorch.

Responsibilities

• Participate in building large-scale recommendation algorithms and systems for TikTok.
• Build long- and short-term user interest models from large datasets.
• Design, develop, evaluate and iterate on 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

Applied ML

Deep Learning

C++/Python

Problem solving

Collaboration

Education

Bachelor's degree in CS or related

Tools

TensorFlow

PyTorch

Job description

TikTok USDS Joint Venture LLC is hiring applied machine learning engineers and data scientists to work on general feed and e-commerce recommendations. The team develops scalable algorithms to boost user engagement and satisfaction, turning innovative ideas into business-impacting solutions.

You will work on large-scale recommendation systems, design user models, and build end-to-end ML pipelines for candidate generation and ranking, including live data processing and feature engineering.