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6 дней назад

Applied AI Researcher (Visual GenAI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Israel
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Applied AI Researcher (Visual GenAI): Developing generative models and computer vision solutions for real-world autonomous driving applications with an accent on visual synthesis, diffusion models, and large-scale proprietary datasets. Focus on adapting state-of-the-art architectures, integrating synthetic data into perception systems, and building scalable Python and PyTorch implementations.

Location: Ramat Gan, Israel; hybrid workplace

Company

hirify.global develops perception and autonomous driving technologies aimed at improving road safety and enabling semi- and fully autonomous vehicles.

What you will do

  • Own the full development lifecycle of generative models, from training to adapting state-of-the-art architectures for autonomous driving use cases.
  • Research, evaluate, and improve Generative AI and computer vision models.
  • Implement scalable and clean solutions in Python and PyTorch.
  • Collaborate with AI researchers and perception teams to integrate synthetic data into real-world applications.
  • Track advancements in AI, generative models, and computer vision.

Requirements

  • Master’s degree or Ph.D. in Computer Science, Electrical Engineering, or a related field.
  • 3+ years of industry experience in deep learning and computer vision.
  • Excellent proficiency in Python and PyTorch.
  • Strong problem-solving, research, and analytical thinking skills.

Nice to have

  • Experience with Generative AI methods, including diffusion models and GANs.
  • Experience with Vision-Language Models and multimodal learning.
  • Publications in top-tier conferences such as CVPR, NeurIPS, or ECCV.
  • Experience with Linux, AWS, Docker, and virtual environments.
  • Knowledge of classic computer vision.

Culture & Benefits

  • Work with massive proprietary datasets and large-scale computing infrastructure.
  • Collaborate with researchers and engineers from multiple disciplines.
  • Develop technology with potential real-world impact on road safety and autonomous mobility.

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