Software Engineer, Computer Vision - Video AI Responsibilities:

• Research, develop, and troubleshoot real time communication systems, related to video and audio codecs, cameras, displays, and microphones
• Work closely with cross-functional teams to understand features, operation, and specify enhancements
• Designing AI/ML-based compression algorithms to reduce the platform's compute footprint, while improving end-user experience
• Optimize and improve video codec efficiency, encode rate control, processing speed, video pre/post-processing, and error resilience
• Debug and diagnose quality of end-to-end video experience on lossy networks in real-time communication scenarios
• Define the video optimization roadmap for both low-end and high-end networks and devices
• Lead the definition and implementation of the media processing pipeline
• Continuously improve the efficiency of the automated test tooling by leveraging the internal automated test infrastructure

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in Computer Science, Computer Engineering, or relevant technical field
• 5+ years software development experience in industry settings or PhD with 2+ years of experience
• 3+ years of experience in computer vision, video/image codecs, video/image processing or a relevant domain
• Experience in neural video/image compression and AI research
• Experience with computer vision, video/image codecs, or video/image processing
• Experience in C/C++ multithreaded programming
• Experience leading large or complex projects, defined goals and delivered milestones by leading teams

Preferred Qualifications:

• Leveraging AI-based enhancement tools that complement standard video-codecs (AV1)
• Knowledge of multimedia stack, including containers, codecs, and AV synchronization
• Experience developing algorithms to improve video quality for calling and video conferencing
• Using ML-based quality metrics and metadata for large-scale quality evaluation
• Experience with state-of-the-art video codecs e.g. H.264/AVC, HEVC, AV1, AV2
• benchmarking of traditional and novel audio/video processing use cases
• Full end-to-end neural-compression techniques at scale, for FoA verticals (Calling, VOD etc.)
• Experience designing power-efficient software for mobile or embedded systems
• Experience with computer vision, video/image codecs, or video/image processing
• Industry experience in Video-on-Demand, RTC, or videos at scale

About Meta: