Research Engineer/Research Scientist, Audio at Anthropic

Hybrid - San Francisco, CA

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Anthropic’s Audio team pushes the boundaries of what's possible with audio with large language models. We care about making safe, steerable, reliable systems that can understand and generate speech and audio, prioritizing not only naturalness but also steerability and robustness.

Salary

USD 350,000 - 500,000

Requirements

Skills

  • Hands‑on experience with training audio models (speech‑to‑speech, speech translation, speech recognition, text‑to‑speech, diarization, codecs, generative audio models)
  • Enjoy research and engineering work with a balanced 50/50 split
  • Comfortable working across abstraction levels, from signal processing fundamentals to large‑scale model training and inference optimization
  • Deep expertise with JAX, PyTorch, or large‑scale distributed training, and ability to debug performance issues across the full stack
  • Thrives in fast‑moving environments where priorities can shift
  • Clear communication and effective collaboration across teams
  • Passionate about building conversational AI that is natural, steerable, and safe
  • Concerned about societal impacts of voice AI
  • Large language model pretraining and finetuning experience
  • Training diffusion models for image and audio generation
  • Reinforcement learning for large language models and diffusion models
  • End‑to‑end system optimization, performance benchmarking and kernel optimization
  • Experience with GPUs, Kubernetes, PyTorch, or distributed training infrastructure

Responsibilities

  • Develop audio codecs and representations
  • Source and synthesize high‑quality audio data
  • Train large‑scale speech language models and large audio diffusion models
  • Develop novel architectures for incorporating continuous signals into LLMs
  • Work across pretraining, finetuning, reinforcement learning, production inference, and product teams
  • Collaborate with multiple internal teams to deploy advanced audio technologies

Technologies

JAXPyTorchLarge‑scale distributed trainingGPUsKubernetesDiffusion modelsAudio codecsSpeech modelsLarge language models

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