Job Description
📋 Description Optimize ASR, LLMs, and TTS for real-world use in noisy environments. Fine-tune LLMs with RAG, RL, and prompts for context-aware chats. Integrate AI components into autonomous agents for scheduling and orders. Implement human-in-the-loop and automated monitoring to improve models. Develop pipelines to construct knowledge graphs from business data. Scale models across GPU/TPU clusters and edge devices to minimize latency. 🎯 Requirements 3-7+ years deploying ML models, ideally in voice, NLP, graphs, or agents. Deep knowledge in speech recognition, LLMs, RL/dialogue, TTS, and ontologies. Proficiency in PyTorch or JAX; CUDA/Triton optimization preferred. Minimize latency and resource use on GPUs/TPUs or edge hardware. Strong data-driven approach with measurable improvements. BS, MS, or PhD in CS, EE, Mathematics, or equivalent. 🎁 Benefits Meaningful equity Real product with real usage and growing revenue In-person culture, fast feedback, and zero bureaucracy Small team that feels like a founding team Health, dental, vision, 401k, life insurance, and unlimited PTO Tools budget, coffee budget, whatever-you-need-to-be-great budget
