Research Engineer/Scientist (all levels), Efficient Models

ByteDance
San Jose
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Skills: ["Communication","Collaboration"]

Work on Vision-Applied Research for ByteDance’s Generative AI and CV/multimodal products. Design and implement efficient large-scale generative model methods focused on large model distillation, compression, scalable training, optimization, and hardware-efficient inference. Build distillation frameworks, accelerate diffusion and autoregressive models, and apply efficiency techniques such as quantization, step/cfg distillation, and other model-architecture approaches to enable deployment at scale.

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FursaFursa
ByteDance
ByteDance
1 month ago

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

Work on Vision-Applied Research for ByteDance’s Generative AI and CV/multimodal products. Design and implement efficient large-scale generative model methods focused on large model distillation, compression, scalable training, optimization, and hardware-efficient inference. Build distillation frameworks, accelerate diffusion and autoregressive models, and apply efficiency techniques such as quantization, step/cfg distillation, and other model-architecture approaches to enable deployment at scale.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Develop efficient algorithms and architectures for large-scale generative and multimodal models using techniques like step distillation, cfg distillation, and quantization.
  • •Advance scalable generative modeling approaches, including diffusion and autoregressive models, with a focus on acceleration and efficiency.
  • •Build distillation frameworks to transfer capabilities from foundation models into smaller, more efficient models.
  • •Enable scalable training, optimization, and deployment of efficient models.
  • •Develop methods for model acceleration and hardware-efficient inference and apply them to use cases like image generation, video generation, and VLM.

Key Requirements

  • •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 research experience, with extensive GenAI/MLSys/LLM experience.
Experience:Generative AILLMsMultimodalModel compressionDiffusion modelsAutoregressive models
Education:
Skills:CommunicationCollaboration
Tech Stack:PyTorchJAXDiffusion modelsAutoregressive modelsQuantizationMixture of Experts (MoE)Window attentionRLHFDPOGRPOImage generationVideo generationVLMMultimodal understanding

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