Research Scientist - TikTok Next Generation Recommendation

Responsibilities
1- Design and develop next-generation large-scale recommendation systems optimized for personalized, engaging, and scalable user experiences.

2-Leverage state-of-the-art machine learning and deep learning techniques, including large model technologies (LLM and MLLM, etc), to enhance recommendation performance and accuracy.

3- Collaborate with cross-disciplinary teams, including infrastructure engineers, PMO, and researchers, to create advanced systems that improve recommendation relevance, diversity, and user engagement.

Qualifications

Minimum Qualifications:
- Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
- Experience in one or more areas of recommender systems, machine learning, computer vision, or natural language processing.
- Familiarity with PyTorch or TensorFlow, solid foundation in data structures and algorithms.

Preferred Qualifications:
- Strong engineering and infrastructure development skills, with hands-on experience in building and optimizing distributed systems and processing large-scale online/offline dataflow.
- Proficiency in CUDA programming (experience with Triton) is highly desirable.
- Proficiency in at least two of the following areas-multimodal content understanding, personalized recommendation, or large-scale cross-domain optimization-is a significant advantage.
- In-depth knowledge and expertise in large-scale Transformer architectures, including mastery of the latest optimization techniques such as Sparse Attention, Linear Attention, Flash Attention, and other cutting-edge methods to enhance model performance and efficiency.
- A strong track record of publications in top-tier conferences, such as CVPR, ACL, KDD, ICML, or NeurIPS.
- Exceptional analytical and problem-solving skills, with the ability to collaborate effectively in cross-functional teams to tackle complex technical challenges.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $187040 - $438000 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.

Client-provided location(s): San Jose, CA

Job ID: TikTok-7521803766221572370

Employment Type: OTHER

Posted: 2025-07-02T00:36:50