Research Scientist/Software Engineer, Neural Graphics and World Models - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

Responsibilities

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.

Team Introduction: Join the TikTok Engine & Tools AI-3D team, where we are building a next-generation AI-native graphics engine for games and interactive experiences across TikTok and future creative platforms. Our work spans 3D asset and scene generation, character animation, physics simulation, neural rendering, and real-time interactive systems, powered by multimodal AI models. We also develop the data pipelines, runtimes, and evaluation frameworks needed to create persistent, controllable, and responsive digital worlds. By combining expertise in machine learning, computer graphics, and large-scale systems, we transform cutting-edge research into practical technologies for the next generation of interactive content.

Topic Content: Graphics rendering serves as core infrastructure for multimedia applications. Amid the rapid growth of short-video and interactive entertainment, the traditional production pipeline-marked by long cycles, high costs, and steep technical barriers-has severely limited creative expression for mainstream users. In recent years, breakthroughs in AIGC (such as emerging representations like NeRF and 3DGS) have driven 3D generation from experimental research toward commercial deployment, establishing it as a critical foundation for future spatial intelligence.
This topic focuses on cutting-edge 3D generation technologies, aiming to evolve the 3D production pipeline from the traditional "modeling-simulation-rendering" workflow to a new AIGC-driven paradigm: "AI Objects - AI Scenes - AI Animation - AI Rendering." Through this transformation, the project seeks to drastically lower barriers to 3D creation, fully empower the interactive entertainment ecosystem, and build a robust technical foundation for spatial intelligence.

Qualifications

Minimum Qualifications:
- Individuals who are completing or have recently completed a PhD degree in computer science, computer engineering, electrical engineering, applied mathematics, or a related discipline.
- Research experience through a laboratory, thesis, publication, internship, open-source project, or substantial independent project.
- Strong, up-to-date foundation in machine learning, generative modeling, and experimental methodology, with hands-on experience building, training, fine-tuning, or evaluating models using frameworks such as PyTorch or JAX.
- Familiarity with modern generative architectures and training methods such as variational autoencoders, latent tokenizers, diffusion or flow-matching models, diffusion transformers, autoregressive models, multimodal transformers, long-context modeling, pre-training, or post-training.
- Engineering fluency with model development workflows and the ability to reason about model architecture, training dynamics, data quality, and evaluation results.
- Deep experience in at least one of the following AI-for-graphics areas: 3D modeling, asset generation, or 3D representations; animation or motion generation; simulation or physics-aware learning; rendering or neural rendering; world models or video prediction; or graphics and game-engine workflows.
- Ability to understand recent research, design controlled experiments, analyze failures, and contribute to model training, data, or evaluation workflows. Interest in collaborating with Software Engineers to move research prototypes into interactive engine pipelines.

Preferred Qualifications:
- Peer-reviewed publications at leading venues such as SIGGRAPH, CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, RSS, CoRL, or related research communities.
- Strong technical reports, open-source contributions, demos, project pages, or research projects that show technical depth, originality, and independent experimentation.
- Experience with 3D or world generation conditioned on text, images, video, actions, or structured scene inputs.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $387600 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.

Responsibilities

Responsibilities

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.

Team Introduction: Join the TikTok Engine & Tools AI-3D team, where we are building a next-generation AI-native graphics engine for games and interactive experiences across TikTok and future creative platforms. Our work spans 3D asset and scene generation, character animation, physics simulation, neural rendering, and real-time interactive systems, powered by multimodal AI models. We also develop the data pipelines, runtimes, and evaluation frameworks needed to create persistent, controllable, and responsive digital worlds. By combining expertise in machine learning, computer graphics, and large-scale systems, we transform cutting-edge research into practical technologies for the next generation of interactive content.

Topic Content: Graphics rendering serves as core infrastructure for multimedia applications. Amid the rapid growth of short-video and interactive entertainment, the traditional production pipeline-marked by long cycles, high costs, and steep technical barriers-has severely limited creative expression for mainstream users. In recent years, breakthroughs in AIGC (such as emerging representations like NeRF and 3DGS) have driven 3D generation from experimental research toward commercial deployment, establishing it as a critical foundation for future spatial intelligence.
This topic focuses on cutting-edge 3D generation technologies, aiming to evolve the 3D production pipeline from the traditional "modeling-simulation-rendering" workflow to a new AIGC-driven paradigm: "AI Objects - AI Scenes - AI Animation - AI Rendering." Through this transformation, the project seeks to drastically lower barriers to 3D creation, fully empower the interactive entertainment ecosystem, and build a robust technical foundation for spatial intelligence.

Qualifications

Qualifications

Minimum Qualifications:
- Individuals who are completing or have recently completed a PhD degree in computer science, computer engineering, electrical engineering, applied mathematics, or a related discipline.
- Research experience through a laboratory, thesis, publication, internship, open-source project, or substantial independent project.
- Strong, up-to-date foundation in machine learning, generative modeling, and experimental methodology, with hands-on experience building, training, fine-tuning, or evaluating models using frameworks such as PyTorch or JAX.
- Familiarity with modern generative architectures and training methods such as variational autoencoders, latent tokenizers, diffusion or flow-matching models, diffusion transformers, autoregressive models, multimodal transformers, long-context modeling, pre-training, or post-training.
- Engineering fluency with model development workflows and the ability to reason about model architecture, training dynamics, data quality, and evaluation results.
- Deep experience in at least one of the following AI-for-graphics areas: 3D modeling, asset generation, or 3D representations; animation or motion generation; simulation or physics-aware learning; rendering or neural rendering; world models or video prediction; or graphics and game-engine workflows.
- Ability to understand recent research, design controlled experiments, analyze failures, and contribute to model training, data, or evaluation workflows. Interest in collaborating with Software Engineers to move research prototypes into interactive engine pipelines.

Preferred Qualifications:
- Peer-reviewed publications at leading venues such as SIGGRAPH, CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, RSS, CoRL, or related research communities.
- Strong technical reports, open-source contributions, demos, project pages, or research projects that show technical depth, originality, and independent experimentation.
- Experience with 3D or world generation conditioned on text, images, video, actions, or structured scene inputs.