ML Engineering Lead: Recommendations & Search

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 209,000 - 616,000; Full time

Benefits offered by this job

In-person work schedule (5 days a week

Comprehensive benefits package

Job summary

TikTok USDS Joint Venture LLC in San Jose, CA is seeking a senior machine learning leader to drive end-to-end recommendation and search models, including candidate generation, ranking, and cold-start solutions. You will recruit, mentor, and manage a high-performing ML Engineering team to push state-of-the-art approaches.

This role emphasizes foundation models/LLMs for feature representation and personalization, requires 5+ years in ML and 2+ years leading teams, and offers a competitive base

Qualifications

• Bachelor's degree in CS/ML/DS or related field
• 5+ years hands-on ML experience focusing on large-scale recommender, search, or ads ranking models
• 2+ years leading engineering teams as Tech Lead or Engineering Manager

Responsibilities

• Drive the technical vision and execution for end-to-end recommendation models, including candidate generation/retrieval, multi-task ranking, re-ranking, and cold-start solutions.
• Explore and integrate cutting-edge ML techniques into recommendation pipelines, such as LLM/Generative AI applications in RecSys, Graph Neural Networks, and modern DLRM.
• Recruit, mentor, and manage a high-performing team of ML Engineers, fostering a culture of algorithmic excellence, scientific rigor, and fast iteration.

Skills

Leadership

Foundation Models / LLMs

Large-scale recommender models

Graph Neural Networks

Education

Bachelor's degree in Computer Science, Machine Learning, Data Science, or related technical field

Job description

TikTok USDS Joint Venture LLC in San Jose, CA is seeking a senior machine learning leader to drive end-to-end recommendation and search models, including candidate generation, ranking, and cold-start solutions. You will recruit, mentor, and manage a high-performing ML Engineering team to push state-of-the-art approaches.

This role emphasizes foundation models/LLMs for feature representation and personalization, requires 5+ years in ML and 2+ years leading teams, and offers a competitive base