Responsibilities
About the Team
The TikTok Recommendation team sits in the center of TikTok, designs, implements and improves the recommendation algorithm that powers the TikTok For You Page (FYP).
The team is at the intersection of cutting-edge machine learning research and large-scale end-to-end production systems. We take pride in finding the right balance between solid applied research, elegant system design and being pragmatic. We have a strong user focus and a dedication to technical excellence.
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
Want more jobs like this?
Get jobs in San Jose, CA delivered to your inbox every week.
What you'll do
- Lead the team to improve recommendation models at massive scale, through applying state-of-the-art machine learning techniques across all ranking phases including but not limited to retrieval, ranking, re-ranking, etc.
- Drive team to apply cutting-edge application-driven research to explore the frontier of recommendation algorithmic domain. Drive team to develop industry leading recommendation systems.
- Drive team to cross functionally work with product managers, data scientists and product engineers to understand insights, formulate problems, design and refine machine learning algorithms, and communicate results to peers and leaders.
- Have a good understanding of end-to-end machine learning systems. Work with infra teams to improve efficiency and stability.
Qualifications
Minimum Qualifications:
- Experience managing teams in one or more of the areas: recommender systems, machine learning, deep learning, pattern recognition, data mining, computer vision, NLP, content understanding or multimodal machine learning
- Good communication and people skills, passionate about driving team direction and taking on challenging problems
Preferred Qualifications:
- Publications at main conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, RecSys or related conferences
- Strong tracking record of success in data mining, machine learning, or ACM-ICPC/NOI/IOI competitions
Participation in public/open-source AI-related projects which are of high visibility
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $224000 - $410000 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.