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EmploymentFull-time
Overview
ABOUT THE ROLE
Full job description
ABOUT THE ROLE This is an early engineering hire at a seed-stage ambient intelligence consumer startup, where you will own the transcription pipeline end-to-end, from audio capture through post-processing. You will work hands-on with product and general management leadership, making real tradeoffs between latency, accuracy, and reliability as the product evolves. WHAT YOU'LL DO
- Build and iterate on a cloud-based ASR pipeline in production at scale, covering audio capture through post-processing.
- Own ASR quality and reliability end-to-end, shipping measurable improvements on latency, small-word accuracy, and voice-print reliability.
- Work across data preparation, model training and fine-tuning, evaluation, and deployment to translate product feedback into shipped pipeline changes.
- Collaborate closely with R&D, hardware, and supply-chain teams across time zones.
- Partner with a Product Engineer on shared backend and pipeline surfaces.
- Operate with minimal specification, turning loosely defined asks into concrete, production-ready improvements. WHAT WE'RE LOOKING FOR
- 3 or more years building and tuning transcription and ASR pipelines end-to-end in production, primarily in cloud-based settings.
- Demonstrated experience with latency-sensitive or streaming audio and ASR pipelines.
- Proficiency across the full ML lifecycle: data handling, model training and fine-tuning, evaluation metrics, and production deployment.
- Experience making latency, accuracy, and reliability tradeoffs in production systems based on real user feedback.
- Comfort working in early-stage or founding engineering environments with minimal specifications and small teams.
- On-device or embedded ML experience (Core ML, TensorFlow Lite, or similar frameworks) is a strong plus.
- Prior experience with wearable, hardware, or robotics device products is a plus.
- Background in AI-native consumer applications focused on transcription or audio is a plus.
- Experience building agent or LLM-based product features, including tool use, memory, or retrieval systems, is a plus. COMPENSATION & BENEFITS Base salary: $150,000 to $200,000 USD annually. Equity participation included. Visa sponsorship is not available. LOCATION Hybrid, 3 days per week in office, in the San Francisco Bay Area, California.
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