Research Engineer​/Scientist Efficient Models

About the Team

The Vision-Applied Research team focuses on applied research in Generative AI and CV/Multimodal Understanding. We deliver intelligent solutions to Tik Tok products, enabling users to create and share creative content more easily. The team comprises research groups dedicated to generative models for content creation, image generation, video synthesis, intelligent image/video editing, and virtual humans.

We are looking for a Research Engineer / Scientist to design and implement efficient models for large-scale generative AI, focusing on large model distillation and compression. You will develop methods and infrastructure to transfer capabilities from foundation models into smaller, more efficient models, enabling scalable training, optimization, and deployment. Responsibilities may include, but are not limited to, distillation frameworks, model acceleration, hardware‑efficient inference, and their applications.

• Develop efficient algorithms and architectures for large-scale generative and multimodal models, using techniques such as step distillation, cfg distillation, quantization, and other methods to improve model efficiency (e.g., image generation, video generation, VLM).
• Advance scalable generative modeling approaches, including diffusion and autoregressive models, with a focus on acceleration and efficiency.

Minimum Qualifications:

• B.S. in Computer Science or related fields, or equivalent experience.
• Expertise in efficient models with deep understanding of computational bottlenecks and acceleration methods.
• Proficiency in training generative AI or LLM models using widely adopted frameworks such as PyTorch and JAX.
• Strong communication and collaboration skills in fast‑paced environments.

• Ph.D. in GenAI, MLSys or equivalent experience.
• Extensive research experience in broad GenAI, MLSys, LLM areas.
• Proven experience in at least one of the following areas: image/video generation and editing; model compression (e.g., quantization, step/cfg distillation); efficient architectures (e.g., MoE, window attention); efficient model design; or reinforcement learning training methods (e.g., RLHF, DPO, GRPO).

Selected city base salary range: $212,800 - $387,600 annually. Compensation may vary outside of this range based on qualifications, skills, competencies, and location. The role may be eligible for additional discretionary bonuses, incentives, and restricted stock units.

Benefits include medical, dental, and vision insurance, a 401(k) plan with company match, paid parental leave, short‑term and long‑term disability coverage, life insurance, wellbeing benefits, and paid holidays and sick days. Details may vary by employment type and country location.

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. Criminal history may influence consideration of duties such as interacting with clients, handling confidential information, and exercising judgment.