Machine Learning Engineer – GAN-Based Image Generative AI

Lit8 develops generative AI systems for real-time image generation and enhancement. In this role, you will focus on developing, training, and improving GAN-based image generation models, with an emphasis on visual quality, stability, controllability, and production-ready performance.We are looking for someone with deep hands-on GAN experience — someone who has trained GANs, debugged adversarial training, improved image quality, and worked directly with generator-discriminator systems.Minimum QualificationsAt least 3 years of hands-on experience working 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, mode collapse mitigation, and image-quality optimization.Experience building or improving image generation, image-to-image, enhancement, super-resolution, inpainting, style transfer, or related visual generation systems.Hands-on experience training, evaluating, and debugging generative models at the model, data, and loss-function level.Strong experience with deep learning for computer vision and image processing.Strong Python programming skills.Hands-on experience with PyTorch or similar deep learning frameworks.Understanding of image quality evaluation, including perceptual quality, artifacts, sharpness, realism, consistency, FID, LPIPS, SSIM, or similar metrics.Strong problem-solving, analytical, and communication skills.Preferred QualificationsExperience with large-scale GAN systems, such as GigaGAN-style architectures, high-resolution GANs, or production-scale image generation models.Experience training GANs on large datasets with distributed training, mixed precision, data curation, and scalable experiment workflows.Experience distilling diffusion models into GAN-based models.Experience optimizing models for low-latency or production inference.Experience with model optimization techniques such as quantization, pruning, distillation, graph optimization, operator fusion, or hardware-aware tuning.Contributions to open-source ML, computer vision, image generation, or GAN-related projects are a plus.Key ResponsibilitiesDevelop, train, and optimize GAN-based image generation models.Improve image quality, realism, sharpness, stability, and controllability.Debug and improve GAN training pipelines, losses, data workflows, and convergence behavior.Evaluate models across visual quality, artifacts, latency, memory usage, and robustness.Collaborate with research, engineering, and product teams to integrate GAN-based models into production applications.What We OfferThe opportunity to work on advanced GAN-based image generative AI systems with real product impact.A fast-moving, research-driven environment focused on technical excellence and ownership.Attractive salary.