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Salary
$200k – $300k per year
Location
In office (San Francisco)
Seniority
Senior · 6+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Pocket is a small AI device that turns everything you say and hear into clear notes, action items, and search. We combine custom hardware, AI, and software to build the best note-taking experience for people who talk and move fast.

Pocket is building a category-defining platform for ambient intelligence. Voice is the highest-signal interface we have - and we’re looking for a research-minded engineer to push what’s possible with voice end-to-end: capture → understanding → real-time experiences → evaluation.

What you'll own

  • Invent and ship improvements to our voice stack: diarization, VAD, noise robustness, transcription quality, speaker ID, and post-processing.
  • Build new voice-powered product capabilities: better memory, better meeting/voice summaries, better action extraction, better personalization.
  • Run tight research loops: define metrics, build eval sets, iterate on models/algorithms, and productionize what works.
  • Improve real-time performance and reliability: streaming pipelines, latency budgets, fallbacks, and graceful degradation.
  • Partner closely with product + design to translate voice capabilities into features people feel immediately.

What success looks like

  • Step-function improvements in voice quality and perceived intelligence (measured and felt).
  • A clear evaluation harness (offline + online) that prevents regressions and accelerates iteration.
  • Voice features that ship reliably at scale with predictable latency.

What we're looking for

  • Have 6-10+ years of experience shipping production systems with strong technical ownership.
  • Are strong in applied ML/research engineering and can turn prototypes into robust product.
  • Understand audio/voice fundamentals (signal processing basics helpful) and modern model/eval workflows.
  • Care deeply about performance and reliability.

Nice-to-haves

  • Experience with streaming audio pipelines and real-time systems.
  • Experience with LLM post-processing, structured extraction, and evaluation.
  • Experience building tooling for labeling, dataset curation, and QA.

What we offer

  • Work directly with us and learn fast
  • Direct impact on how the company operates day to day
  • High-trust, high-responsibility environment
  • Competitive compensation
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