Design and integrate vision encoders and audio-native models into agent reasoning loops, optimize streaming latency for voice-to-voice interactions, and architect multimodal RAG systems to retrieve insights from videos and PDFs while ensuring efficient cross-modal alignment.
We are seeking a talented Multimodal AI Systems Architect to develop and optimize AI systems that seamlessly integrate vision and audio models. This role focuses on enhancing our voice-to-voice interactions and multimodal retrieval capabilities, ensuring our systems are efficient and innovative.
Responsibilities:
- Integrate vision encoders and audio-native models into core agent reasoning loops.
- Optimize streaming latency for voice-to-voice AI interactions.
- Architect multimodal RAG systems capable of retrieving insights from videos and PDFs.
Qualifications:
- Experience with Whisper, CLIP, and multimodal LLM integration.
- Knowledge of streaming architectures and WebRTC.
- Expertise in cross-modal alignment.
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