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AI Video Research Engineer Intern

Tether.io
Found 2 months ago
Location
Tallinn, Estonia
Duration (Months)
3 Months
Time
Not disclosed
Work Mode
Remote
Salary
null
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master
  • PhD

Skills & Qualifications

Technical Skills

  • PyTorch
  • deep learning
  • image generation
  • video generation
  • multimodal learning
  • open-source video foundation models
  • large-scale or distributed training
  • diffusion-based
  • transformer-based
  • hybrid video generation models

Soft Skills

  • analytical thinking
  • creativity
  • collaboration skills

Job Description

We are seeking highly motivated MSc or PhD interns to work on video generation and multimodal video foundation models. Interns will focus on one or more components of the foundation model lifecycle and are encouraged to propose creative, research-driven ideas that advance the state of the art. You will contribute to the development and improvement of open-source video foundation models, analyze their limitations, and design scalable solutions. This is a research-focused internship with opportunities to publish at top-tier computer vision and machine learning conferences, and to work with petabyte-scale video datasets and large distributed GPU clusters with thousands of GPUs.

Requirements

  • MSc or PhD candidate in Computer Science, Machine Learning, Computer Vision, or a related technical field
  • Research topic or experience in image generation, video generation, or multimodal learning
  • Awareness of open-source video foundation models and their current limitations
  • Proficiency with PyTorch and modern deep learning workflows
  • Strong analytical thinking, creativity, and collaboration skills
  • Prior first-author related publications in CVPR, ICCV, ECCV, NeurIPS, or ICLR
  • Demonstrated related work, such as research codebase or benchmarks released on GitHub or similar platforms
  • Experience with large-scale or distributed training
  • Hands-on experience with diffusion-based, transformer-based, or hybrid video generation models

Related Field

  • AI & Machine Learning

Related Subfield

  • Computer Vision

Languages

  • English

Nice to Haves

  • Demonstrated related work, such as research codebase or benchmarks released on GitHub or similar platforms
  • Experience with large-scale or distributed training
  • Hands-on experience with diffusion-based, transformer-based, or hybrid video generation models
▶Apply Now

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