Sr. Research Engineer/Scientist (all levels), Efficient Models

ByteDance
Seattle
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Education: bachelorsSkills: ["Communication","Collaboration"]

Build efficient generative and multimodal model methods for large-scale content creation. Work on distillation and compression to transfer capabilities from foundation models into smaller models, enabling scalable training, optimization, and deployment. Develop distillation frameworks, model acceleration, and hardware-efficient inference, advancing generative modeling approaches such as diffusion and autoregressive models with a focus on efficiency and real-world impact.

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ByteDance
ByteDance
1 month ago

Sr. Research Engineer/Scientist (all levels), Efficient Models

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 31 days agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Build efficient generative and multimodal model methods for large-scale content creation. Work on distillation and compression to transfer capabilities from foundation models into smaller models, enabling scalable training, optimization, and deployment. Develop distillation frameworks, model acceleration, and hardware-efficient inference, advancing generative modeling approaches such as diffusion and autoregressive models with a focus on efficiency and real-world impact.
Location: Seattle
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Design and implement efficient algorithms and architectures for large-scale generative and multimodal models.
  • •Improve model efficiency using techniques such as step distillation, cfg distillation, and quantization for applications like image and video generation and VLM.
  • •Advance scalable generative modeling approaches, including diffusion and autoregressive models, focused on acceleration and efficiency.
  • •Develop infrastructure and methods for transferring capabilities from foundation models to smaller, more efficient models.
  • •Contribute to distillation frameworks, model acceleration, and hardware-efficient inference and their applications.

Key Requirements

  • •B.S. in Computer Science or related fields, or equivalent experience.
  • •Deep expertise in efficient models, including understanding computational bottlenecks and acceleration methods.
  • •Proficiency training generative AI or LLM models using tools/frameworks such as PyTorch and JAX.
  • •Strong communication and collaboration skills in fast-paced environments.
  • •Experience in image/video generation and editing, model compression (e.g., quantization, step/cfg distillation), efficient architectures (e.g., MoE, window attention), efficient model design, or RL training methods (e.g., RLHF, DPO, GRPO).
Experience:Generative AILLMsComputer visionMultimodalModel compressionImage generationVideo generation
Education:Bachelor's in Computer Science
Skills:CommunicationCollaboration
Tech Stack:PyTorchJAXQuantizationDiffusionAutoregressiveMoEWindow attentionRLHFDPOGRPO

Company Brief

ByteDance
Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Headquarters: Beijing, China
Founded: 2012
WebsiteLinkedIn