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Hedra

Research Scientist, Video Generation Distillation

Hedra, San Francisco

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About Hedra
Hedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence.

About Hedra
Hedra is a pioneering generative media company backed by top investors at Index, A16Z, and Abstract Ventures. We're building Hedra Studio, a multimodal creation platform capable of control, emotion, and creative intelligence.
At the core of Hedra Studio is our Character-3 foundation model, the first omnimodal model in production. Character-3 jointly reasons across image, text, and audio for more intelligent video generation — it’s the next evolution of AI-driven content creation.
At Hedra, we’re a team of hard-working, passionate individuals seeking to fundamentally change content creation and build a generational company together. We value startup energy, initiative, and the ability to turn bold ideas into real products. Our team is fully in-person in SF/NY with a shared love for whiteboard problem-solving.
Overview
We are seeking a Research Scientist to lead innovation in video generation distillation, including step distillation, model size reduction, and efficient inference methods. This role focuses on making state-of-the-art video diffusion models faster, lighter, and more deployable without sacrificing quality. The ideal candidate will be experienced in model compression techniques and capable of bridging cutting-edge research with production needs.
Responsibilities

  • Research and develop distillation techniques for video diffusion models, including step distillation, layer pruning, and knowledge transfer.
  • Optimize models for latency, memory footprint, and energy efficiency while maintaining high generation quality.
  • Collaborate with engineering to implement and benchmark accelerated inference pipelines.
  • Monitor and evaluate advancements in model compression, quantization, and efficient generative modeling.
  • Present findings to the team and contribute to publications or patents where applicable.
Qualifications
  • PhD or strong industry experience in Machine Learning, with a focus on model compression, distillation, or efficient deep learning.
  • Strong understanding of diffusion models and their training/inference workflows.
  • Proficiency in Python and PyTorch; familiarity with performance profiling and optimization.
  • Experience with quantization, pruning, and low-rank adaptation techniques is a plus.
  • A record of impactful work in model efficiency, either in research or production.
Benefits
  • Competitive compensation + equity
  • 401k (no match)
  • Healthcare (Silver PPO Medical, Vision, Dental)
  • Lunch and snacks at the office
We encourage you to apply even if you don't meet every requirement — we value curiosity, creativity, and the drive to solve hard problem

Seniority level

  • Seniority level

    Mid-Senior level

Employment type

  • Employment type

    Full-time

Job function

  • Job function

    Other
  • Industries

    Technology, Information and Internet

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