Responsibilities

We are Creative AI team under Monetization Technology. Our team focuses on developing cutting-edge Generative AI techs across all modalities, including text, image, videos, landing pages, etc., and creates industry-leading technical solutions to improve creative efficiency for advertisers, agencies and creators. We are committed to automated creative workflows by leveraging Generative AI technologies, to increase overall revenue for advertisers, agencies and creators. We aim to drive and lead generative AI in the ads tech and creative industry, powering products and driving values for our clients, creators, and the whole ecosystem. We are looking for infrastructure engineers who are excited to grow their business understanding, build highly scalable and reliable software/infrastructure, partner across functions with global teams, and make big impacts. If you are someone who welcomes challenges, we are eager to have you on the team! We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities: - Lead research in advancing technology in large language model or multimodality generative model architectures; - Research, implement and evaluate novel machine learning algorithms on generative models; - Collaborate with applied machine learning teams and infrastructure teams to ship new generative models into ad production.

Qualifications

Minimum Qualifications - Individuals who are completing or have recently completed a PhD degree in Computer Science or a related discipline. - Hands-on experience of developing multimodality foundation models and work or internship experience in an AI research organization is a plus - Strong publications record in top conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, etc) By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

Job Information

[For Pay Transparency]Compensation Description (Annually)

The base salary range for this position in the selected city is $128000 - $256000 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.