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Uber Logo Uber · IT - Software Development

Staff Voice AI Engineer

United States, San Francisco 232000.00 - 258000.00 USD / Year · Job Posted March 04, 2026
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Job Description

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.

Job Responsibility

  • 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 processing services, and evaluation harnesses for voice quality
  • Own Voice AI systems in production end-to-end, including rollout strategies, monitoring, alerting, quality regression detection, and on-call readiness
  • Collaborate closely with product, design, and research teams to translate user needs into Voice AI capabilities with measurable business and customer impact

Requirements

  • 10+ years of experience in software engineering, data science, or machine learning, including a track record of shipping production AI systems
  • Deep understanding of large language models, including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG)
  • Strong backend and distributed systems expertise, with experience designing and operating highly available, scalable services in production
  • Deep experience with ML infrastructure, including model training pipelines, online serving systems, feature stores, experiment platforms, and evaluation frameworks
  • Hands-on experience with distributed data processing systems (e.g., Spark, Flink, Ray) and workflow orchestration (e.g., Airflow or equivalent)
  • Ability to analyze data, run experiments, and derive insights for model and product improvement
  • Excellent communication and collaboration skills across technical and non-technical teams

Nice to have

  • Experience building evaluation frameworks for Voice AI, including metrics and human/LLM-assisted evaluations for speech recognition accuracy, latency, robustness, and naturalness of synthesized speech
  • Demonstrated expertise in machine learning fundamentals applied to voice, including model evaluation, training, and fine-tuning of ASR, TTS, or speech-language models
  • Proven experience deploying Voice AI systems to production, with an emphasis on low-latency, high-reliability, real-time environments
  • Experience writing developer documentation, creating voice-specific SDKs, or enabling internal teams to build on shared Voice AI platforms
  • Hands-on work with large-scale audio datasets, including data curation, labeling strategies, and optimization of voice processing pipelines at scale

What we offer

  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible to participate in a 401(k) plan
  • Eligible for various benefits (details at link)
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