Machine Learning Engineer

• Design, develop, and optimize video generation and editing models using diffusion techniques, focusing on consistency, realism, and style
• Build scalable pipelines for training and deploying video models
• Work closely with other teams on large-scale video datasets, including human motion, gestures, facial expressions, and scene context
• Experiment with cutting-edge diffusion architectures for controllable and high-quality video synthesis
• Define robust validation strategies and implement custom evaluation metrics comparing synthetic and real footage
• Contribute to foundational MLOps practices and infrastructure: experiment tracking, CI/CD, deployment, monitoring, and versioning
• Help build infrastructure for experiment tracking, reproducibility, distributed training, model serving, and production deployment
• Hands-on across the full ML development cycle, from research implementation to production monitoring

ML Engineer, Video Generation

AI Engineer, Full-Stack

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Senior MLOps Engineer