Senior Machine Learning Engineer

Responsibilities:
Research & Develop: Design and implement state-of-the-art generative models, including Diffusion Models, 3D VAEs and GANs for AI-powered media synthesis End-to-End Content Generation: Build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models Speech & Video Synchronization: Develop advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content Real-Time AI Systems: Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques Scaling & Production Deployment: Work closely with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) Collaboration & Research: Stay ahead of the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality Experimentation & Validation: Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, and refine model architectures Code Quality & Best Practices: Participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development Qualifications: Bachelor's or Masters degree in Computer Science, Machine Learning, or a related field 3+ years of experience working with deep generative models, including Diffusion Models, 3D VAEs, GANs and autoregressive models Strong proficiency in Python and deep learning frameworks such as PyTorch Expertise in multi-modal AI, text-to-image, and image-to-video generation, audio to lipsync Strong understanding of machine learning principles and statistical methods