Machine Learning Engineer – GAN-Based Image Generative AI
Il y a 19 heures
France
LIT8
Temps plein
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Lit8 develops generative AI systems for real-time image generation and enhancement. In this role, you will develop, train, and improve GAN-based image generation models, focusing on visual quality, training stability, controllability, and production-ready performance.
We are looking for someone with deep hands-on GAN expertise — someone who has trained GANs, debugged adversarial training, and improved generator-discriminator systems in practice, rather than simply using pretrained models.
Minimum Qualifications
• At least 3 years of hands-on experience with GANs, including training, fine-tuning, debugging, and optimizing GAN-based image generation models.
• Strong practical experience with generator-discriminator training, adversarial losses, training stability, and mode collapse mitigation.
• Experience building image generation, image-to-image, super-resolution, enhancement, or related visual generation systems.
• Hands-on experience designing training pipelines, improving loss functions, and evaluating generative models.
• Strong understanding of image quality evaluation, including FID, LPIPS, SSIM, perceptual quality, and visual artifacts.
• Strong Python programming skills and proficiency with PyTorch.
• Strong analytical and problem-solving skills. Preferred Qualifications
• Experience with large-scale GAN architectures, such as GigaGAN, or other high-resolution image generation systems.
• Experience training GANs on large datasets using distributed training, mixed precision, and scalable data pipelines.
• Experience distilling diffusion models into GAN-based generators or combining adversarial training with diffusion distillation.
• Experience optimizing GANs for low-latency or production inference.
• Knowledge of quantization, pruning, operator fusion, or hardware-aware optimization.
• Contributions to open-source GAN or image generation projects.
Key Responsibilities
• Develop, train, and optimize GAN-based image generation models.
• Improve image realism, visual quality, training stability, and controllability.
• Debug and refine adversarial training, loss functions, and data pipelines.
• Evaluate architectures and benchmark image quality and inference performance.
• Collaborate with research and engineering teams to integrate models into production applications.
What We Offer
• The opportunity to work on advanced GAN-based image generation systems with real product impact.
• A research-driven environment focused on technical excellence and ownership.
• Attractive salary. If you are passionate about GANs and have substantial experience training high-quality generative models, we'd love to hear from you.
• At least 3 years of hands-on experience with GANs, including training, fine-tuning, debugging, and optimizing GAN-based image generation models.
• Strong practical experience with generator-discriminator training, adversarial losses, training stability, and mode collapse mitigation.
• Experience building image generation, image-to-image, super-resolution, enhancement, or related visual generation systems.
• Hands-on experience designing training pipelines, improving loss functions, and evaluating generative models.
• Strong understanding of image quality evaluation, including FID, LPIPS, SSIM, perceptual quality, and visual artifacts.
• Strong Python programming skills and proficiency with PyTorch.
• Strong analytical and problem-solving skills. Preferred Qualifications
• Experience with large-scale GAN architectures, such as GigaGAN, or other high-resolution image generation systems.
• Experience training GANs on large datasets using distributed training, mixed precision, and scalable data pipelines.
• Experience distilling diffusion models into GAN-based generators or combining adversarial training with diffusion distillation.
• Experience optimizing GANs for low-latency or production inference.
• Knowledge of quantization, pruning, operator fusion, or hardware-aware optimization.
• Contributions to open-source GAN or image generation projects.
Key Responsibilities
• Develop, train, and optimize GAN-based image generation models.
• Improve image realism, visual quality, training stability, and controllability.
• Debug and refine adversarial training, loss functions, and data pipelines.
• Evaluate architectures and benchmark image quality and inference performance.
• Collaborate with research and engineering teams to integrate models into production applications.
What We Offer
• The opportunity to work on advanced GAN-based image generation systems with real product impact.
• A research-driven environment focused on technical excellence and ownership.
• Attractive salary. If you are passionate about GANs and have substantial experience training high-quality generative models, we'd love to hear from you.