Senior Machine Learning Engineer - Generative AI

• Design and develop advanced generative models including Diffusion Models, GANs, 3D VAEs, and autoregressive models for AI-powered media synthesis.
• Build and optimize end-to-end content generation pipelines for high-fidelity image, video, and lip-sync generation.
• Develop multimodal AI systems that integrate speech, video, and facial animation for hyper-realistic content output.
• Implement and fine-tune models for real-time performance, using techniques such as model quantization, pruning, and distillation.
• Collaborate with engineering teams to deploy AI models on scalable cloud platforms (AWS, GCP, Azure).
• Conduct rigorous experimentation to improve model accuracy, realism, and computational efficiency.
• Stay updated with the latest research in deep generative models, transformer-based vision systems, and multimodal AI.
• Participate in code reviews, maintain high standards of code quality, and document key findings to support internal knowledge sharing.

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
• Minimum 3 years of hands-on experience working with deep generative models (Diffusion Models, GANs, VAEs).
• Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Proven experience in text-to-image, image-to-video, and audio-to-lip-sync model development.
• Solid understanding of machine learning principles, statistical modeling, and neural network architectures.
• Familiarity with real-time inference optimization and deployment on cloud environments (AWS, GCP, Azure).
• Experience working with multimodal architectures and transformer-based models like CLIP, BLIP, or GPT-4V.
• Contributions to open-source projects or peer-reviewed publications in generative AI, speech synthesis, or video generation are a plus.

PyTorch

AWS

Google Cloud Platform (GCP)

Azure