Research Scientist – Recommendation; NextGen LLM; Global Frontier Tech Prog

Responsibilities

We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.

Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.

Our team's mission is to empower GenAI and content understanding in Tik Tok businesses. Computer vision and natural language processing are important dimensions in both content generation and understanding. We are working on various foundational models, including multi-modality pretraining, multi-modal large language model, image generation, video generation etc. As a GenAI team on the business side, we try to succeed in both achieving business metric gains (recommendation metrics), and also producing state-of-the-art research outputs.

• Recommendation Large Models:
  Address challenges such as gradient convergence and representation drift in ultra-long behavioral sequences, enabling the system to achieve true "logical reasoning" capabilities.
• Unified Multimodal Semantic Space:
  Explore alignment across video, image-text content, and user intent, constructing a fully multimodal semantic space that goes beyond text.
• Agentic Rec:
  Develop recommendation agents with capabilities such as self-reflection, tool invocation, and long-horizon planning, driving a transformation of recommendation and content distribution experiences.

• Extreme-scale reasoning:
  Performance gains and bottlenecks associated with ultra-large model parameters and ultra-long sequence modeling.
• Multimodal fusion:
  Challenges in representation learning for cross-modal intent alignment.
• Autonomous evolution:
  Breakthroughs in long-horizon planning and decision-making paradigms for agent systems.

• Technical value:
  Explore new paradigms for recommendation, significantly improving recommendation performance and system efficiency.
• Business value:
  Enable deeper understanding of user interests and content, improving distribution efficiency and enhancing satisfaction for both users and creators.

• Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
• Experience in one or more areas of computer vision, natural language processing and machine learning.
• Solid knowledge and experience with at least one major deep learning framework (e.g. PyTorch, Tensorflow, MXNet, Caffe/Caffe2).
• Familiar with deep neural network architectures such as transformer/SSM/CNN/RNN/LSTM etc.
• Strong analytical and problem solving skills. Ability to work collaboratively in cross-functional teams.

• Degree in computer science, electrical engineering or related fields.
• Authors with publications in top-tier venues such as SIGGRAPH, SIGGRAPH Asia, CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR.

Compensation: Base salary range: $212,800 - $450,000 annually. Compensation may vary outside this range depending on a number of factors, including qualifications, skills, competencies, experience and location. Base pay is one part of the total package which may include discretionary bonuses, incentives, and restricted stock units.

Benefits: 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, 10 paid sick days and 17 days of paid personal time (prorated upon hire).

We reserve the right to modify or change these benefits programs at any time, with or without notice.

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:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues.
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems.
• Exercising sound judgment.