ASR Engineer
AI Summary
Builds and owns a cloud-based automatic speech recognition pipeline end-to-end, tuning transcription quality, latency, and reliability for a consumer AI hardware and software product.
About this role
About the Role
This is a foundational engineering role at an early-stage AI consumer hardware and software startup, where you will own the transcription pipeline end-to-end. You will work hands-on with product and general management leadership to build, tune, and ship a cloud-based ASR system with a narrowly scoped on-device component. Your work directly shapes how well the core product experience feels to real users.
What You'll Do
Build and iterate on the cloud-based ASR pipeline, from audio capture through post-processing, running 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 preparation, model training and fine-tuning, evaluation, and deployment to translate product feedback into shipped pipeline changes.
Collaborate with a Partner Product Engineer on shared backend and pipeline surfaces.
Coordinate across time zones with R&D, hardware, and supply-chain teams based in China.
Operate with minimal specification, turning informal asks into concrete, shipped 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 ownership of production ASR systems across the full lifecycle: data preparation, model training and fine-tuning, evaluation, and deployment.
Experience building and optimizing latency-sensitive or streaming audio and ASR pipelines.
Track record of making latency, accuracy, and reliability tradeoffs based on real user feedback.
Experience debugging and tuning transcription quality issues in production environments.
Comfort shipping in early-stage or founding engineering environments with small teams and limited specification.
On-device or embedded ML experience using frameworks such as Core ML or TensorFlow Lite.
Prior experience with wearable, hardware, or robotics device products.
Background at AI-native consumer applications focused on transcription or audio.
Experience building agent or LLM-based product features including tool use, memory, or retrieval systems.
Ability to work hybrid three days per week in the San Francisco Bay Area.
Ability to collaborate asynchronously with international teams across time zones.
Compensation & Benefits
Salary range: $150,000 to $200,000 USD annually. Visa sponsorship is not available for this role.
Location
Hybrid, three days per week on-site in the San Francisco Bay Area, California, United States.
Skills
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