
About the Role You'll own the transcription pipeline end-to-end at an early-stage ambient intelligence startup — a cloud-based ASR system with a narrowly scoped on-device component. As one of the first US engineering hires, you'll work hands-on with product and leadership to build, tune, and ship pipeline improvements that directly shape the core product experience. What You'll Do Build and iterate on the cloud-based ASR pipeline, from audio capture through post-processing, in production at scale. Own ASR quality and reliability end-to-end, shipping measurable improvements across latency, small-word accuracy, and voice-print reliability. Work across data, training/fine-tuning, evaluation, and deployment to translate product feedback into shipped pipeline changes. Collaborate with overseas R&D, hardware, and supply-chain teams across time zones. Partner with a product-focused backend engineer on shared pipeline surfaces. Operate with minimal specification — turning lightweight asks into concrete, production-ready improvements. What We're Looking For 3+ years building and tuning transcription/ASR pipelines end-to-end in production, primarily in cloud-based settings. Demonstrated ownership of production ASR systems across the full lifecycle: data preparation, model training/fine-tuning, evaluation, and deployment. Experience building and optimizing latency-sensitive or streaming audio/ASR pipelines. Track record of shipping pipeline improvements from design through deployment based on real production usage data. Comfort making latency, accuracy, and reliability tradeoffs based on genuine user feedback — not just benchmark scores. Prior experience at an early-stage or founding-team engineering environment with minimal specifications and small teams. On-device or embedded ML experience (e.g. Core ML, TensorFlow Lite, or similar frameworks) is a plus. Background in wearable, hardware, or robotics device products is a plus. Experience at an AI-native consumer application focused on transcription or audio is a plus. Experience building agent or LLM-based product features (tool use, memory, retrieval) is a plus. Location Hybrid (3 days/week in office) — San Francisco Bay Area, CA. Visa sponsorship is not available.
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