Research Engineer​/Scientist Efficient Models

Overview

The Vision-Applied Research team focuses on applied research in Generative AI and CV/Multimodal Understanding, and delivering intelligent solutions to Byte Dance products, enabling users to make and share creative content in a much easier way. The team has research groups dedicated to generative models for content creation, image generation, video synthesis, intelligent image/video editing, and virtual humans.

The team is looking for a Research Engineer/Scientist who can take initiatives in designing and implementing efficient models for large-scale generative AI, with a particular emphasis on large model distillation and compression. The candidate will work on developing methods and infrastructure for transferring 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.

• 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 and tools such as PyTorch and JAX.
• Strong communication and collaboration skills in fast-paced environments.

• Ph.D. in GenAI, MLSys or equivalent experience
• Extensive research experiences in broad GenAI, MLSys, LLM areas.
• Proven experiences 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).

Founded in 2012, Byte Dance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including Tik Tok, Lemon8, Cap Cut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, Byte Dance has made it easier and more fun for people to connect with, consume, and create content.

Inspiring creativity is at the core of Byte Dance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

As Byte Dancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Byte Dance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At Byte Dance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach.

We are passionate about this and hope you are too.

Byte Dance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a…