The posting, in Decagon's own words
archived Sep 4, 2026About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.
Read more about the Speech Research Team's work:
https://decagon.ai/blog/audio-native-semantic-speaker-change-detection https://decagon.ai/blog/scaling-real-time-tts-inference https://decagon.ai/blog/teaching-flow-matching-tts-with-rl The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.
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About the Role
As a Research Engineer focused on Audio and Speech, you’ll be responsible for building the models and agent harnesses that power Decagon’s real-time voice agents and taking them all the way from idea to production. Your work will advance multimodal and full-duplex systems that can listen, reason, speak, and respond naturally in real time. We’re looking for strong engineers who want to build the next generation of AI voice agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions. In this role, you will Design and build next-generation agent harnesses optimized for streaming speech, turn-taking, interruptions, overlapping speech, and continuous interaction Research and train multimodal and full-duplex models that jointly understand audio, reason, and generate speech Improve speech recognition, voice activity detection, endpointing, and speech generation across diverse speakers, environments, domains, and languages Build evaluations and use production calls to ship measurable improvements in accuracy, latency, naturalness, and task outcomes Optimize end-to-end inference for responsiveness, throughput, stability, and cost, partnering with Voice Platform and Infrastructure teams to deploy at scale Your background looks something like this 2+ years of experience in speech, audio ML, multimodal ML, or production Experience developing or adapting autoregressive, diffusion, flow-matching, or codec-based speech models Hands-on experience with streaming agent systems, low-latency inference, production model serving, and evaluation on real-world audio Fluency in Python and a modern deep-learning framework such as , with strong foundations in and signal processing A track record of taking research ideas from prototype to reliable, measurable production impact Even better if you have Familiarity with speech-to-speech or full-duplex models Experience with telephony, multilingual speech, noisy-channel robustness, speaker adaptation, or expressive speech generation