Machine Learning Engineer, Search Recommendation

TikTok’s Search Growth team is building the search recommendation engine behind TikTok and TikTok Mall, with the goal of improving how people discover products and understand what they are searching for. In this onsite role in San Jose, you will work on machine learning models that power recommendation across the end-to-end search workflow, from early retrieval to final ranking.

Role summary

You will develop and enhance search recommendation algorithms and models to increase TikTok and TikTok Mall search traffic while strengthening users’ search understanding. The work emphasizes hyperscale machine learning approaches and explores how short text and general recommendation techniques can be pushed further, especially where recommendation and NLP meet.

Responsibilities

• Improve search recommendation services and models for TikTok, increasing search traffic on TikTok and TikTok Mall and enhancing users’ understanding of search.
• Optimize recommender systems using hyperscale machine learning models across an end-to-end workflow, including recall/first-stage ranking through final-stage ranking.
• Investigate the upper bounds of short text recommendation and broader recommendation technology, with attention to interactions between recommendation and NLP technology.

Requirements

• 3+ years of work experience in machine learning, with good product sense and a focus on user experience.
• Bachelor or advanced degree in computer science or a related technical discipline.
• Excellent coding skills, along with solid knowledge of data structures and algorithms.
• Strong analytical, modeling, and problem-solving ability, including the capability to identify the core of problems from complex data.

Technologies

• Machine learning, NLP, CV, recommendation, multi-modal technology
• Hyperscale machine learning models

Team context

The Search Growth team is leading development of the search recommendation algorithm for TikTok’s rapidly expanding global e-commerce enterprise. Using advanced machine learning technology along with NLP, CV, recommendation, and multi-modal technology, the team is focused on delivering a top-tier e-commerce search experience to over 1 billion active TikTok users worldwide.

Mission statement: to create a world where there are no hard-to-sell, overpriced products.

Compensation

For pay transparency, the base salary range for this position in the selected city is $122,574 - $316,800 annually. Compensation may vary outside of this range based on factors such as qualifications, skills, competencies, experience, and location. Base pay is part of the total package and this role may be eligible for additional discretionary bonuses/incentives and restricted stock units. Benefits may vary depending on the nature of employment and country work location, and TikTok reserves the right to modify or change benefits programs at any time.

Benefits

• Day one access to 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 upon hire with increasing accruals by tenure)
• Additional discretionary bonuses/incentives, and restricted stock units (may be eligible)

Los Angeles County (Unincorporated) Fair Chance notice

• 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.
• The company notes that criminal history may have a direct, adverse, and negative relationship on job duties, potentially resulting in the withdrawal of a conditional offer of employment.
• Examples of duties referenced include interacting and occasionally having unsupervised contact with internal or external clients and colleagues, appropriately handling and managing confidential information, and exercising sound judgment.