Research Engineer - TikTok Ads Core ML, Ranking

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) match

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Paid holidays

Paid sick days

Paid personal time

Job summary

TikTok Inc. is seeking a Research Engineer to join the Ads Core ML Ranking team in California. You will work on ML/RL/LLM based ranking models to maximize delivery efficiency and revenue, collaborating with product and business teams across the globe.

Ideal candidates hold a CS/Math degree, are proficient in C/C++ and Python, and have experience with TensorFlow or PyTorch, Hadoop, and Spark. Strong problem solving and curiosity about new tech are essential.

Qualifications

• BS/MS in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields/with related experience.
• Research/industry experience in ML, DL, statistical models or applied math methods.
• Solid programming skills in C/C++ and Python; knowledge of data structures and algorithms.
• Familiar with ML frameworks (TensorFlow/PyTorch/MXNet).
• Familiarity with online experimentation and analytics; big data systems including Hadoop and Spark.
• Curiosity about learning and applying new technologies.

Responsibilities

• Optimize efficiency across the entire advertising funnel (Recall/Rough-sort, Fine-sort, CTR/CVR).
• Research and develop global advanced advertising delivery systems using ML/DL/RL/LLM.
• Design and set up system framework and standards to improve efficiency and meet business needs.
• Collaborate with product and business teams globally.

Skills

C/C++

Python

Online experimentation

Machine learning

Deep learning

Education

BS/MS in CS/Statistics/OR Applied Math

Tools

TensorFlow

PyTorch

MXNet

Hadoop

Spark

Job description

Responsibilities

TikTok Ads Core ML Team aims at creating automatic delivery products for the next generation and developing advertising as a global business, instead of just a monetization tool to consolidate the delivery funnel framework allowing multiple teams to iterate parallel.

We're looking for innovative Research Engineers focused on ML/RL/LLM or other relevant professional domains, to join our TikTok Ads Core ML Ranking team. Ads Core Ranking team specifically focuses on maximizing delivery system efficiency and revenue growth through state-of-the-art models and frameworks. Our research topics include but not limited to: Generative Retrieval and Large Recommendation Model, LLM-based Ranking Application, and Optimization of System Resource Allocation with ROI target.

As part of our team, you will be responsible for:

• Optimize efficiency across the entire advertising funnel, including Recall&Rough-sort, Fine-sort(CTR/CVR), format/creative personalization and system resource allocation.
• Research & develop a global advanced advertising delivery system through frontier technologies, including ML/DL, RL, LLM and also scaling law in ads recommendation.
• Design & Set up system framework and standard to continuously improve overall efficiency and meet different vertical business needs.
• Work with product and business teams from various scenarios with global impact.

All of our team effort, is to continuously pursue and establish a world-leading ranking model & framework that always benefits our collaborators, users and customers to get better returns.

Qualifications

Minimum Qualifications:

• BS/MS degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields/with related experience.
• Research/industry experience in one or more of the following areas: machine learning, deep learning, statistical models and applied mathematical methods etc.
• Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms.
• Familiar with at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet).
• Familiarity with online experimentation and analytics. Familiarity with big data systems including Hadoop and Spark.
• Curiosity towards learning and applying new technologies.

Preferred Qualifications:

• Participation in national math/coding competitions (ACM/Hacker Cup/Hash Code/USACO/IOI/CCPC etc.).
• Paper publications/citations in NLP/CV/Recommender System(RecSys/KDD/ICML/CVPR/NeurIPs, etc.).
• Experience in LLM, reinforcement learning, transfer learning, and counter-factual optimization is a plus.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $316800 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.

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.