Research Engineer, Audio and Speech

Decagon
San Francisco +1 more
On-site

Who this role is best for

Aimed at mid-to-senior level engineers with speech/audio ML expertise who want to build real-time voice agents and work in-office.

Best fit for

  • Candidates with 2+ years in speech ML and a history of deploying research into production
    — “2+ years of experience in speech, audio ML, multimodal ML, or production machine learning”
  • Individuals experienced in training autoregressive or diffusion-based speech models
    — “Experience developing or adapting autoregressive, diffusion, flow-matching, or codec-based speech models”
  • Engineers fluent in Python and PyTorch with a focus on signal processing and ML
    — “Fluency in Python and a modern deep-learning framework such as PyTorch, with strong foundations in machine learning and signal processing”

Things to consider

  • In-office work is required, which may limit remote flexibility for candidates
    — “We’re an in-office company, driven by a shared commitment to excellence and velocity”
  • The role demands ownership of technical decisions and end-to-end project delivery
    — “People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions”

How to stand out

  • Highlight experience with streaming speech and low-latency inference systems in your resume
    — “Design and build next-generation agent harnesses optimized for streaming speech”
  • Emphasize measurable production impact from research in your interview responses
    — “A track record of taking research ideas from prototype to reliable, measurable production impact”
  • Showcase familiarity with multimodal and full-duplex systems in your application materials
    — “Research and train multimodal and full-duplex models that jointly understand audio, reason, and generate speech”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designing and building agent harnesses
  • researching and training multimodal models
  • improving speech recognition and generation
Typical background
speech, audio ML experiencehands-on experience developing or adapting speech models

Skills & requirements

Required

Speech, Audio MLMultimodal MLSpeech RecognitionVoice Activity DetectionEndpointingSpeech Generation

Preferred

Autoregressive ModelsDiffusion ModelsFlow-matching ModelsCodec-based Speech Models

Stack & domain

Speech, Audio MLMultimodal MLProduction Machine LearningAutoregressive ModelsDiffusion ModelsFlow-matching ModelsCodec-based Speech ModelsSpeech RecognitionVoice Activity DetectionEndpointingSpeech GenerationStreaming SpeechTurn-takingOverlapping SpeechContinuous InteractionFull-duplex SystemsReal-time Voice AgentsMultimodal And Full-duplex ModelsEnd-to-end InferenceResponsivenessThroughputStabilityCost OptimizationLeadershipTechnical Decision-makingTeamworkCommunicationAI Voice Agents

About the role

Original posting from Decagon via Ashby

About 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.

About the 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.

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 machine learning
  • 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 PyTorch, with strong foundations in machine learning 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

Compensation

$200K – $400K + Offers Equity

Benefits

We proudly offer the following benefits for our full-time employees:

  • Medical, Dental, and Vision benefits for you and your family
  • Life Insurance and Disability Benefits
  • Retirement Plan (e.g., 401K, pension)
  • Parental Leave
  • Fertility and family building benefits through Carrot
  • Monthly stipend to support your wellness, lifestyle, and work-life balance
  • Daily lunches and snacks in the office to keep you at your best
  • Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)

These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Source: Decagon careers (Ashby)

Similar roles

More roles at Decagon