About the Role
You'll own the transcription pipeline end-to-end at an early-stage ambient intelligence consumer hardware startup, covering a cloud-based ASR system with a narrowly scoped on-device component. This is one of the first US engineering hires, and you'll work directly with the GM and Head of Product to build, tune, and ship pipeline improvements. You'll make real tradeoffs between latency, accuracy, and reliability as the product evolves.
What You'll Do
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Build and iterate on the cloud-based ASR pipeline, from audio capture through post-processing, in production at scale.
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Own ASR quality and reliability end-to-end, shipping measurable improvements on latency, small-word accuracy, and voice-print reliability.
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Work across data, training and fine-tuning, evaluation, and deployment to turn product feedback into shipped pipeline changes.
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Collaborate closely with China-based R&D, hardware, and supply-chain teams across time zones.
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Partner with the product engineer on shared backend and pipeline surfaces.
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Operate with minimal specification, turning loosely defined asks into concrete, production-ready improvements.
What We're Looking For
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3+ years building and tuning transcription or ASR pipelines end-to-end in production, primarily in cloud-based settings.
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Demonstrated ownership of production ASR systems through the full lifecycle: data preparation, model training and fine-tuning, evaluation, and deployment.
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Experience building and optimizing latency-sensitive or streaming audio/ASR pipelines.
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Comfortable making latency, accuracy, and reliability tradeoffs based on real user feedback, not just benchmark results.
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Track record of shipping pipeline improvements from design through deployment and iteration.
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Early-stage or founding engineering experience; able to ship without large team support or fully specified requirements.
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On-device or embedded ML experience (Core ML, TensorFlow Lite, or similar frameworks).
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Prior experience building wearable, hardware, or robotics device products.
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Background in AI-native consumer applications focused on transcription or audio.
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Experience building agent or LLM-based product features, including tool use, memory, or retrieval systems.
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Ability to collaborate asynchronously across time zones.
Compensation & Benefits
Salary range: $150,000 to $200,000 USD annually. Visa sponsorship is not available for this role.
Location
Hybrid, 3 days per week in office. San Francisco Bay Area, California, US.
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