Research Scientist, Large Recommender Models-TikTok Recommendation

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You'll be joining the TikTok Recommendation team focusing on advancing large-scale recommender systems that power TikTok's personalized content discovery and user experiences. By developing cutting-edge models, we aim to optimize recommendation accuracy, user engagement, and scalability across billions of users. We're looking for Machine Learning Scientists passionate about building high-performance, scalable recommendation systems. You'll leverage advanced deep learning techniques and large-scale systems engineering, collaborating with cross-functional teams to solve complex challenges in personalization and recommendation at scale.

Responsibilities

1. Research and develop large-scale recommender systems for personalized, engaging user experiences, focusing on scalability, accuracy, and performance.
2. Apply advanced machine learning and deep learning techniques to optimize recommendation algorithms for TikTok's diverse user base.
3. Manage the end-to-end lifecycle of recommender models, from training and fine-tuning to deployment, monitoring, and continuous improvement.
4. Analyze complex data to uncover user preferences, behaviors, and trends, driving personalization and enhancing TikTok's recommendation capabilities.
5. Collaborate with cross-functional teams (infrastructure, product, research, etc.) to design and implement innovative solutions that improve the relevance and diversity of TikTok recommendations.

Qualifications

Minimum Qualifications

1. Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
2. Experience in one or more areas of recommender systems, machine learning, computer vision, or natural language processing.
3. Proficiency in programming skills, solid foundation in data structures and algorithms.
4. Strong familiarity with deep learning architectures such as transformers, CNNs, RNNs, LSTMs, etc.
5. Excellent analytical and problem-solving skills, with the ability to collaborate effectively in cross-functional teams.

Preferred Qualifications

1. Ph.D. in Computer Science, Electrical Engineering, or related fields.
2. Experience in building large-scale recommender systems that handle vast, diverse datasets and complex user interactions.
3. Publications in top-tier venues such as RecSys, SIGGRAPH, CVPR, ICCV, ICML, NeurIPS, ICLR, or similar conferences/journals.

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://shorturl.at/cdpT2

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $145000 - $355000 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.