Team & Project Introduction: We are developing a next-generation AI-powered video editing tool designed to make high-quality video creation accessible to everyone. At the core of this initiative is an intelligent assistant embedded within creative workflows, capable of understanding user intent and automating complex editing tasks. As a member of this mission-driven team, you will collaborate with a tight-knit group of researchers and engineers working at the intersection of machine learning, video editing systems, and creative technology. Responsibilities: - Design and develop a next-generation video editing framework that seamlessly integrates AI automation with manual editing workflows. - Build intelligent agent systems that accurately interpret user intent and orchestrate AI-driven video editing operations. - Work closely with researchers to support model training, performance benchmarking, and iterative improvement based on real-world user feedback. - Integrate state-of-the-art LLM and generative AI advancements into the video editing pipeline to power new capabilities and improve user experience. - Partner with product designers to envision and implement innovative UI strategies that elevate the creative experience.
Minimum Qualifications: - Master’s degree or PhD in Computer Science, Machine Learning, or a related field. - Practical experience in training and evaluating machine learning models, particularly in video understanding or generative tasks. - Familiarity with data processing workflows and building robust pipelines for model training and inference. - Solid understanding of AI agents and LLM integration, including task planning, multimodal input handling, and agent-driven interaction. - Proven ability to apply AI capabilities to real-world product scenarios, delivering robust and scalable user-facing features. Preferred Qualifications: - Demonstrated experience in developing advanced AI systems, with a focus on applying machine learning in real-world, user-facing applications. - Direct experience leveraging AI in domains closely tied to video editing, such as automated editing, scene understanding, or content generation. - Deep understanding of multimedia frameworks and tools, including video pipelines, encoding/decoding technologies, and real-time media processing. - Proven ability to bridge AI model development with scalable product engineering in cross-functional teams. - Strong research or engineering contributions in areas such as LLM-driven agents, video synthesis, or AI-enhanced creative tools.
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