Demo

Researcher: Audio

Cartesia
San Francisco, CA Full Time
POSTED ON 3/4/2025
AVAILABLE BEFORE 5/27/2025

About Cartesia

Our mission is to build the next generation of AI : ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text-1B text tokens, 10B audio tokens and 1T video tokens-let alone do this on-device.

We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.

We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90 angels across many industries, including the world's foremost experts in AI.

The Role

  • Conduct pioneering research at the intersection of audio signal processing, machine learning, and generative modeling to push the boundaries of voice AI systems.
  • Develop cutting-edge algorithms for tasks such as speech enhancement, echo cancellation, denoising, and voice activity detection, leveraging generative approaches like diffusion models, VAEs, or autoregressive frameworks.
  • Design novel methods for end-to-end modeling of audio signals, exploring advancements in neural audio synthesis, speech representation learning, and self-supervised training paradigms.
  • Lead the development of robust evaluation pipelines to analyze performance, validate real-world effectiveness, and identify future research directions.

What We're Looking For

  • Deep expertise in audio signal processing, generative modeling, and machine learning, with a proven track record of publishing impactful research in top-tier conferences (e.g., NeurIPS, ICASSP, ICLR).
  • Proficiency in frameworks such as PyTorch, TensorFlow, or specialized tools for audio processing like torchaudio or librosa.
  • Strong understanding of state-of-the-art generative techniques, including diffusion models, autoregressive models, flow-based models, etc.
  • Passion for solving complex problems in speech and audio, with a focus on creating innovative and practical solutions for noisy, multi-modal, or real-time environments.
  • Excellent collaboration and communication skills, with the ability to work effectively in research-driven and cross-functional teams.
  • Nice-to-Haves

  • Experience building audio models that have been used in production at scale.
  • Background in hardware-aware optimization for deploying real-time audio models.
  • Early-stage startup experience or experience working in fast-paced R&D environments.
  • Our culture

    We're an in-person team based out of San Francisco. We love being in the office, hanging out together and learning from each other everyday.

    We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don't sacrifice quality and design along the way.

    We support each other. We have an open and inclusive culture that's focused on giving everyone the resources they need to succeed.

    Our perks

    Lunch, dinner and snacks at the office.

    Fully covered medical, dental, and vision insurance for employees.

    401(k).

    Relocation and immigration support.

    Your own personal Yoshi.

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