About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
We're building the infrastructure that lets people talk to Claude—real-time, bidirectional voice conversations that feel natural, responsive, and safe. This is foundational work for how millions of people will interact with AI.
The Voice Platform team designs and operates the serving systems, streaming pipelines, and APIs that bring Anthropic's audio models from research into production across Claude.ai, our mobile apps, and the Anthropic API. You'll work at the intersection of real-time media, low-latency inference, and distributed systems—building infrastructure where every millisecond of latency is felt by the user.
We partner closely with the Audio research team, who train the speech understanding and generation models, and with product teams shipping voice experiences to users. Your job is to make those models fast, reliable, and delightful to talk to at scale.
What you'll do
- Design and build the real-time streaming infrastructure that powers voice conversations with Claude—ingesting microphone audio, orchestrating model inference, and streaming synthesized speech back with minimal latency
- Build low-latency serving systems for speech models, optimizing time-to-first-audio and end-to-end conversational responsiveness
- Develop the public and internal APIs that expose voice capabilities to Claude.ai, mobile clients, and third-party developers
- Own the audio transport layer—codecs, jitter buffers, adaptive bitrate, packet loss recovery—so conversations stay smooth across unreliable networks
- Build observability and quality-measurement systems for voice: latency distributions, audio quality metrics, interruption handling, and turn-taking accuracy
- Partner with Audio research to move new model architectures from experiment to production, and feed real-world performance data back into research
- Collaborate with mobile and product engineering on client-side audio capture, playback, and the end-to-end user experience
You may be a good fit if you
- Have 6+ years of experience building distributed systems, real-time infrastructure, or platform services at scale
- Have shipped production systems where latency is measured in tens of milliseconds and users notice when you miss
- Are comfortable working across the stack—from transport protocols and serving infrastructure up to the APIs product teams build on
- Are results-oriented, with a bias toward flexibility and impact
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming (we love to pair!)
- Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly
- Are comfortable with ambiguity—voice is a fast-moving space, and you'll help define the architecture as we learn what works
Strong candidates may also have experience with
- Real-time media protocols and stacks: WebRTC, RTP, gRPC bidirectional streaming, or WebSockets at scale
- Audio engineering fundamentals: codecs (Opus, AAC), voice activity detection, echo cancellation, jitter buffering, or audio DSP
- Low-latency ML inference serving, streaming model outputs, or GPU-based serving infrastructure
- Telephony, live streaming, video conferencing, or voice assistant platforms
- Mobile audio pipelines on iOS (AVAudioEngine, AudioUnits) or Android (Oboe, AAudio)
- Working alongside ML researchers to productionize models—speech experience is a plus but not required
Representative projects
- Driving time-to-first-audio below human perceptual thresholds by co-designing the serving pipeline with the Audio research team
- Building a streaming inference orchestrator that interleaves speech recognition, LLM reasoning, and speech synthesis with overlapping execution
- Designing the voice mode API surface for the Anthropic API so developers can build their own voice agents on Claude
- Implementing graceful barge-in and interruption handling so users can cut Claude off mid-sentence naturally
- Instrumenting end-to-end audio quality metrics and building dashboards that catch regressions before users do
Deadline to apply: None. Applications will be reviewed on a rolling basis.
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
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