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Research Scientist, Addressee Detection / Speech Separation

Between

Remote · location unlistedFull-timePosted 2mo agoStill listed 4 days ago

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At a glance

Compensation
No compensation found
Location
Remote · location unlisted
Role Type
Research
Schedule
Full-time
Work Authorization
Not specified

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Job overview

Between is hiring a Research Scientist, Addressee Detection / Speech Separation. The Research Scientist will advance the company's approach to addressee detection and speech separation in complex, real-world audio environments. This role involves framing challenging problems, conducting focused experiments, and translating results into shippable models. The scientist will also build datasets and benchmarks, partner with engineering for production integration, and ensure scientific integrity in product development.

Key focus areas include Advance approach to addressee detection and speech separation in crowded, overlapping, real world audio, Frame hard problems clearly, run focused experiments, and turn results into models, and Build datasets and benchmarks that let us tell real progress from noise.

Successful candidates bring Depth In Speech Audio, Track Record Of Modeling, and Comfort With Messy Audio. Important skills include Addressee Detection, Speech Separation, Machine Learning, Clear Thinking, and Clear Writing. Preferred (not required): Source Separation, Robust Speech, and Acoustic Scene Analysis.

Skills & qualifications

RequiredNice to have

Skills

Addressee DetectionSpeech SeparationMachine LearningClear ThinkingClear WritingSource SeparationRobust SpeechAcoustic Scene Analysis

Qualifications

Depth in Speech, Audio, or Closely Related Area of Machine LearningTrack Record of Taking Hard Modeling Problems From Idea to ResultComfort Working With Real, Messy AudioInterest in Seeing Research Reach Real Users QuicklyPublished or Shipped Work in Source Separation, Robust Speech, or Acoustic Scene Analysis

Full job description

Careers

Research Scientist, Addressee Detection / Speech Separation Remote · Full-time · Research

You will push the frontier on multi-speaker audio: separating overlapping voices and determining who is talking to the machine versus to another person in the room. Your work becomes the core of a product, not a paper that sits on a shelf.

Apply What you will do

  • Advance our approach to addressee detection and speech separation in crowded, overlapping, real world audio.

  • Frame the hard problems clearly, run focused experiments, and turn the results into models we can ship.

  • Build the datasets and benchmarks that let us tell real progress from noise.

  • Partner closely with engineering so that what works in research survives contact with production.

  • Keep us honest about what the science can and cannot do yet. What we are looking for

  • Depth in speech, audio, or a closely related area of machine learning, whether from research, industry, or both.

  • A track record of taking hard modeling problems from idea to result.

  • Comfort working with real, messy audio rather than only clean benchmarks.

  • Clear thinking and clear writing; you can explain a tradeoff to an engineer and to a customer.

  • Interest in seeing your research reach real users quickly, at a small company.

  • Bonus: published or shipped work in source separation, robust speech, or acoustic scene analysis. About attention labs

attention labs is early: a small team defining a new category at the intersection of speech, cognitive neuroscience, and machine learning. We work from San Francisco, Toronto, and Memphis, and we are remote-friendly for the right person.

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