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Video AI Engineer
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Video AI Engineer
Builds advanced artificial intelligence solutions for video processing, neural rendering, and avatar generation to enhance real-time communication platforms and video conferencing experiences
Key Responsibilities:
- Conduct full-stack research and development, translating state-of-the-art video AI research into production-ready features
- Build and deploy video processing applications across desktop and mobile platforms including Mac, Windows, iOS, and Android
- Design, implement, and maintain modular algorithms within video processing pipelines ensuring scalable and clean code
- Apply deep knowledge of neural rendering, generative models, diffusion models, and Gaussian Splatting for video enhancement
- Optimize video processing algorithms for speed and performance across various hardware platforms and devices
- Evaluate algorithm performance through research, testing, and real-world usage while refining based on user feedback
- Collaborate with global teams to innovate and enhance video AI technologies for communication platforms
Skills & Tools:
- Neural rendering and generative AI models (diffusion, discriminative models)
- Image and video processing frameworks and libraries
- Multi-platform development (Mac, Windows, iOS, Android)
- Computer vision and machine learning techniques
- Transfer learning and Gaussian Splatting methodologies
- Multi-threaded programming and real-time processing
- Multimedia stream data processing workflows
- Performance optimization and hardware acceleration
- Strong research and publication experience in top-tier conferences
Where This Role Has Appeared:
- Zoom (Video Conferencing, San Jose, CA, $127-$255/hour, July 2025)
Variants & Related Titles:
- Computer Vision Engineer - Video
- Real-time Video AI Developer
- Video Enhancement Engineer
- Neural Rendering Engineer
- Video ML Engineer
Why This Role Is New:
Video AI Engineer emerged in 2020-2022 as video conferencing became essential for work and social interaction during the pandemic, driving demand for AI-powered video enhancements. The role evolved from traditional computer vision work to focus specifically on real-time video processing challenges like avatar generation, background replacement, and video quality enhancement that require specialized expertise in neural rendering and generative models.
Trend Insight:
As video communication becomes the default mode of interaction for work and social engagement, companies are investing heavily in AI-powered video technologies that can create more engaging, personalized, and high-quality video experiences in real-time.
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