Responsibilities
About the team
On the TikTok Search Team, you will have the opportunity to develop and apply cutting edge machine learning technologies in real-time large-scale systems, which serve billions of search requests every day. Via advanced NLP and multi-modal models, our projects impact and improve the search experience for hundreds of millions of users globally. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
The main job directions include:
1. Exploring and developing large-scale language models and optimizing enterprise applications to the extreme;
2. Data construction, instruction tuning, preference alignment, and model optimization;
3. Implementation of relevant applications, including content generation, summary etc.;
Want more jobs like this?
Get jobs in San Jose, CA delivered to your inbox every week.
4. Collaborating with cross-functional teams to produce and apply new science to more responsibly develop and deploy large language models
5. In-depth research and exploration of more usage scenarios in future life.
Responsibilities:
- Conduct research and develop state-of-the-art algorithms in various stages of the development of LLM, including continued pretraining, SFT, RLHF;
- Investigate and implement robust evaluation methodologies to assess model performance at various stages, unravel the underlying mechanisms and sources of their abilities, and utilize this understanding to drive model improvements.
- Using inference stage techniques such as RAG, CoT, Prompt Engineering to improve the model output
- Improve the performance of AI Search in the TikTok app to provide better search experience for users
Qualifications
Minimum qualifications:
• Bachelor or advanced degree in computer science or a related technical discipline.
• Effective communication and teamwork skills.
• Proficient coding skills and strong algorithm & data structure basis.
Preferred qualifications:
- 5+ years of related industry experience.
- Experience in one or more of the following areas is preferred: NLP, LLM, RL
- Candidates with top-tier conference papers, including ICML, NeurIPS, ICLR, CVPR, ICRA, KDD etc., relevant internship experience or winners of ACM competitions are preferred;
- Experience in using data-driven methods to enhance the capability of LLMs through various stages of the model development
- Experience in RAG, Prompt Engineering or other inference time methods to enhance the performance of the system
Job Information
[For Pay Transparency] Compensation Description (annually)
The base salary range for this position in the selected city is $194000 - $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.