Machine Learning Engineer, Recommendation - E-Commerce

Benefits

• Medical, dental, and vision insurance
• 401(k) savings plan with company match
• Paid parental leave
• Short-term and long-term disability coverage
• Life insurance
• Wellbeing benefits
• 10 paid holidays per year
• 10 paid sick days per year
• 17 days of Paid Personal Time, prorated at start with accruals increasing with tenure

Based in San Jose, CA on site, this role offers a competitive salary range of USD 150,000 to 316,800 per year and provides a collaborative environment across the TikTok Shop recommendation ecosystem.

Responsibilities

• Develop and refine optimization strategies for a large-scale e-commerce recommendation pipeline covering 10 million to 100 million products or creators' contents
• Build long and short term user interest models, extracting insights from vast, diverse data to efficiently reveal latent interests
• Design, implement, evaluate and iterate on predictive models for candidate generation and ranking, including CTR and CVR prediction, with real-time data pipelines, feature engineering, model optimization and innovation
• Create supporting and debugging tools as needed

Requirements

• Bachelor's degree in computer science or a related field, or higher
• 3+ years of experience with a solid foundation in data structures and algorithms, and proficiency in Python, Java, C++, R, or similar
• Familiar with common machine learning, deep learning, causal inference, and operational optimization algorithms, including classification, regression, and clustering, as well as mathematical programming and heuristic methods
• Experience with at least one framework such as TensorFlow, PyTorch, or MXNet, including training and deployment details, and training acceleration methods like mixed precision and distributed training
• Familiar with big data frameworks; experience with MapReduce or Spark is preferred

Technologies

• Python, Java, C++, R
• TensorFlow, PyTorch, MXNet
• MapReduce, Spark

Teams

• E-commerce - Recommendation and Marketing
• E-commerce - Alliance
• E-commerce - Search
• E-commerce - Search Growth

Fair Chance Act Notice for Los Angeles County Candidates

Qualified applicants with arrest or conviction records will be considered for employment in accordance with federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Criminal history may influence certain job duties, potentially affecting the conditional offer of employment, including interactions with clients or colleagues, handling confidential information and access to information systems, and exercising sound judgment.