Machine Learning Engineer - Measurement Signal and Privacy Technology

Responsibilities

Our Ads Measurement Signal and Privacy team (MSP) is missioned to build our security and governance infrastructure and process for the ads system end-to-end while making sure our platform with large volume of various signals and data are constantly compliant with regional regulations across the world. The team will be responsible for exploring and implementing cutting-edge privacy-enhancing technologies to protect our users while keeping TikTok a free and creative community. You will be a key player in data privacy, protection, security and managing cross-functional programs to continuously improve the process.

Responsibilities:
By joining us, you'll have the opportunity to participate in the development of algorithms and systems for one of the world's leading ranking and recommendation services. Your work will mainly include:
1. Developing advanced ML and LLM algorithms (including retrieval, ranking, calibration modules) for signal matching systems at the scale of millions of QPS
2. Iterating and optimizing ranking algorithms and strategies through data analysis and experimentation.
3. Leading the development and operational work of large-scale, distributed real-time systems for testing, integrating, and deploying machine learning models.
4. Creating algorithms and data-driven solutions that utilize one of the world's richest user behavior datasets for various ads-related use cases, such as ads ranking, targeting, bidding, calibration, and reporting.
5. Collaborating with product teams to define product strategies and features.

Qualifications

Minimum Qualifications:
1. Bachelor's or Master's degree in Computer Science, Computer Engineering, or related fields from an internationally renowned university.
2. Proficient in one or more general-purpose programming languages, including but not limited to: Go, C/C++, Python.
3. Experience in machine learning/deep learning algorithm development at large internet companies in one of the following areas: search, ads, or recommendation.

Preferred Qualifications:
1. PhD and research experience in AI fields such as ML, NLP, CV.
2. Experience of engineering development experience for systems at millions of QPS scale
3. Experience leading complex projects with successful delivery.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $156000 - $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.