Research Engineer: Generative AI & Model Compression

ByteDance; San Jose (CA); On-site; USD 209,000 - 616,000; Full time

Benefits offered by this job

Job summary

ByteDance Vision-Applied Research team seeks a Research Engineer/Scientist to design and implement efficient models for large-scale generative AI, with emphasis on distillation and compression. The role includes building methods and infrastructure for transferring capabilities from foundation models into smaller, efficient forms for scalable training and deployment.

The candidate will work on distillation frameworks, model acceleration, hardware-efficient inference, and related applications,

Qualifications

• B.S. in Computer Science or related fields or equivalent experience.
• Expertise in efficient models with understanding of bottlenecks and acceleration.
• Proficiency in training generative AI or LLM models using PyTorch and JAX.
• Strong communication and collaboration in fast-paced environments.

Responsibilities

• Develop efficient algorithms and architectures for large-scale generative and multimodal models leveraging distillation and quantization.
• Advance scalable generative modeling approaches with a focus on acceleration and efficiency.

Skills

Efficient models

Model acceleration

Communication

Education

B.S. in Computer Science or related fields

Ph.D. in GenAI or MLSys

Tools

PyTorch

JAX

Job description

ByteDance Vision-Applied Research team seeks a Research Engineer/Scientist to design and implement efficient models for large-scale generative AI, with emphasis on distillation and compression. The role includes building methods and infrastructure for transferring capabilities from foundation models into smaller, efficient forms for scalable training and deployment.

The candidate will work on distillation frameworks, model acceleration, hardware-efficient inference, and related applications,