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 Master’s 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.