Design, train, and fine-tune Generative AI models (e.g., GANs, VAEs, Diffusion Models, Transformers like GPT, Stable Diffusion).
Develop and optimize large-scale deep learning models for text, image and video generation.
Implement efficient training pipelines using distributed computing and cloud-based infrastructure (e.g., AWS, GCP).
Research and experiment with foundation models, multimodal AI, and reinforcement learning to enhance generative capabilities.
Collaborate with synthetic data engineers to preprocess datasets, create synthetic data, and optimize data pipelines.
Deploy generative AI models into production using ML frameworks (TensorFlow, PyTorch) and MLOps best practices.
Optimize model inference for latency and efficiency, leveraging quantization, pruning, and edge deployment strategies.
Stay updated with cutting-edge AI research, contribute to patents/publications, and participate in open-source projects.
Work closely with product teams to integrate generative AI into real-world applications (e.g., content creation, automation, digital assistants).