15 hours ago

Research Engineer/Scientist (all levels), Efficient Models

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Work on the Vision-Applied Research team to develop efficient generative AI and multimodal models for content creation. Design and implement large model distillation and compression methods that transfer capabilities from foundation models to smaller, faster models, enabling scalable training, optimization, and deployment. Build distillation frameworks, improve model acceleration, and develop hardware-efficient inference approaches for image/video generation, VLMs, and related applications.

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.
•Create and improve distillation frameworks and methods for transferring capabilities from foundation models to smaller, more efficient models.
•Work on model acceleration and hardware-efficient inference for applications such as image generation, video generation, and VLMs.
•Support scalable training, optimization, and deployment of efficient generative models.

Key Requirements

•B.S. in Computer Science or related fields, or equivalent experience.
•Expertise in efficient models, including a 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.
•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 AIComputer VisionMultimodalLarge Language Models (LLMs)

Education:Bachelor's

Skills:CommunicationCollaboration

Tech Stack:PyTorchJAXDiffusion modelsAutoregressive modelsQuantizationMoEWindow attentionRLHFDPOGRPO

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

15 hours ago

Research Engineer/Scientist (all levels), Efficient Models

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

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.
•Create and improve distillation frameworks and methods for transferring capabilities from foundation models to smaller, more efficient models.
•Work on model acceleration and hardware-efficient inference for applications such as image generation, video generation, and VLMs.
•Support scalable training, optimization, and deployment of efficient generative models.

Key Requirements

•B.S. in Computer Science or related fields, or equivalent experience.
•Expertise in efficient models, including a 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.
•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 AIComputer VisionMultimodalLarge Language Models (LLMs)

Education:Bachelor's

Skills:CommunicationCollaboration

Tech Stack:PyTorchJAXDiffusion modelsAutoregressive modelsQuantizationMoEWindow attentionRLHFDPOGRPO

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn