Machine Learning Engineer, Commerce Ads

Machine Learning Engineer, Commerce Ads at TikTok in San Jose, CA.

Responsibilities

TikTok commerce ads team holds a strong advertiser focus and a dedication to technical excellence. We work with advertisers from all verticals, such as E-commerce, Retail, Travel etc, to make TikTok an irreplaceable growth channel for businesses of all sizes and a favorite destination for consumers to discover and purchase products, content, and services. We are on the critical path to delivering TikTok's Ads revenue and working on building the next-generation web ads solution for TikTok.

We are seeking Machine Learning Engineers who can help us to improve our existing delivery system that optimizes for advertisers' true business objectives, i.e. desired user value and effectiveness of ROI. You will have a chance to work with a fully globalized team made up of great engineering talents in different countries, and work closely with cross-functional teams to build proper and relevant connections between users, advertisers, and TikTok.

• Build highly scalable machine learning systems and state-of-the-art machine learning models to improve ads ranking quality and optimize advertisers' marketing strategies. Examples include but are not limited to click through rate prediction, conversion rate prediction, intelligent format selection and user journey optimization.
• Explore, develop and experiment with new features to improve model accuracy.
• Understand ads platform objectives and take full advantage of modern machine learning to improve ads relevance, quality, and quantity delivered to end-users.
• Collaborate with Product Managers, Designers, and other disciplines to explore the next generation of shopping experiences on TikTok.

Requirements

• BS/MS degree in Computer Science, Computer Engineering, or other relevant majors, with related work experience.
• Solid programming skills, including but not limited to: Go, C/C++, Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
• Good analytical thinking capability. Have essential knowledge and skills in statistics.
• Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM, etc.).
• Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet), familiar with its architecture and implementation mechanism.

Preferred Qualifications

• Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB).
• Experience in resource management and task scheduling with large-scale distributed software (such as Spark and TensorFlow).
• Relevant work or research experiences in search and recommendation.

Job Information

[For Pay Transparency] Compensation Description (annually)

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, 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 the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.

Additional Information

For Los Angeles County (unincorporated) Candidates

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.