Generative AI Engineer, Image/Video Restoration
Generative AI Engineer, Image/Video Restoration
Posted on :
12-09-2025
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1 Vacancy
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Job Description
- Research design and implement generative AI models for image and video restoration (e.g. deblurring denoising super-resolution inpainting frame interpolation).- Build and optimize training pipelines for large-scale datasets including preprocessing augmentation and distributed training.- Evaluate restoration performance using both objective metrics (PSNR SSIM LPIPS) and subjective/perceptual quality measures.- Develop scalable and efficient inference pipelines optimizing for latency throughput and memory.- Stay current with the latest research in computer vision and generative AI and translate novel ideas into practical solutions.- Collaborate with cross-functional teams to integrate restoration models into production systems.
- Education: Masters or Ph.D. in Computer Science Electrical Engineering Applied Mathematics or a related field.
- Strong background in computer vision and deep learning with proven experience in generative models (diffusion GANs transformers).
- Proficiency in Python and deep learning frameworks (PyTorch preferred).
- Experience with large-scale image/video datasets and distributed training (multi-GPU or multi-node).
- Solid understanding of image and video restoration metrics (PSNR SSIM LPIPS) and perceptual evaluation.
- Hands-on experience with video preprocessing such as motion estimation and optical flow frame alignment and stabilization temporal consistency techniques and video encoding/decoding.
- Strong software engineering skills: clean code Git debugging optimization.
- Track record of publications or open-source contributions in generative AI computer vision or image/video restoration.
- Experience with real-world video data processing (e.g. raw domain HDR pipelines ISP sharpening).
- Familiarity with cloud-based large-scale dataset management (e.g. S3 distributed file systems).
- Experience with real-time or near-real-time video restoration and performance optimization.
- Knowledge of advanced motion analysis (scene change detection temporal consistency checks optical flow with RAFT/PWC-Net).
- Familiarity with deployment on diverse hardware (edge devices mobile GPU acceleration).
- Practical experience with efficient model deployment including model compression quantization distillation and hardware optimization (e.g. TensorRT mixed precision).
Employment Type
Full Time
Key Skills
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