ML Engineer - E-commerce Feed & Live Recommendations

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 317,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) with company match

Paid parental leave

Disability coverage

Life insurance

Wellbeing benefits

10 paid holidays per year

10 paid sick days per year

Paid Personal Time

Job summary

TikTok Inc. is hiring for a team focused on interest-based E-commerce recommendations for the TikTok Shop platform.

You will contribute to live-streaming and short video recommendations that connect customer interests with quality sellers and products. The role involves building scalable ML-powered models, exploring user interests, and improving the shopping experience through real-time data pipelines and feature engineering.

Qualifications

• Bachelor's degree or higher in Computer Science or related field.
• Strong programming and problem-solving ability.
• 1 year of experience in applied machine learning.
• Experience with TensorFlow or PyTorch.
• Experience with C++ or Python.

Responsibilities

• Participate in building large-scale live-streaming and short video e-commerce recommendation algorithms and systems on TikTok.
• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking, including data pipelines and feature engineering.
• Build long and short term user interest models and extract information from large data to explore latent interests.
• Develop strategies using ML to improve user shopping experience and address challenges like cold start and traffic allocation.
• Design and build supporting/debugging tools as needed.

Skills

Programming skills

ML experience

Deep learning tools

C++/Python

Education

Bachelor's in Computer Science

Tools

TensorFlow

PyTorch

Job description

TikTok Inc. is hiring for a team focused on interest-based E-commerce recommendations for the TikTok Shop platform.

You will contribute to live-streaming and short video recommendations that connect customer interests with quality sellers and products. The role involves building scalable ML-powered models, exploring user interests, and improving the shopping experience through real-time data pipelines and feature engineering.