Staff Voice AI Engineer - Applied AI

Staff Voice AI Engineer - Applied AI Department: Engineering Team: Machine Learning Location: San Francisco, United States Type: Full-Time **About the Role:** Applied AI at Uber builds intelligent systems that power next-generation product experiences for riders, drivers, merchants, and couriers. As a Staff Voice AI Engineer, you will lead the design and deployment of large-scale, real-time Voice AI systems that enable natural, reliable, and intelligent voice interactions across Uber’s ecosystem. You will operate as a full-stack technical leader across speech modeling, LLM-powered conversational intelligence, and low-latency backend infrastructure — owning Voice AI systems end-to-end, from model development and evaluation to highly available, distributed production services. This includes advancing capabilities in automatic speech recognition (ASR), text-to-speech (TTS), spoken language understanding, and LLM-driven dialogue systems. You will partner closely with product, design, and infrastructure teams to translate customer pain points into seamless voice-first experiences — setting the foundation for how Voice AI is built, deployed, and operated across Uber’s global platform. **What You Will Do:** - Design and build end-to-end Voice AI solutions, from understanding customer pain points and defining product requirements to deploying LLM-powered, real-time voice interfaces in production. - Benchmark and evaluate voice AI systems, including speech recognition, speech synthesis, and spoken language understanding, by designing evaluations, analyzing results, and identifying systematic weaknesses. - Improve voice model performance through system prompt tuning, fine-tuning voice- and speech-specific models, and optimizing architectures for low-latency, real-time voice interactions. - Analyze voice request logs, prompt traces, and audio inputs to diagnose failure modes, improve transcription accuracy, conversational quality, and overall user experience. - Build and maintain internal tools and platforms to automate Voice AI workflows, such as large-scale transcription pipelines, real-time audio processi