Staff Engineer
Aqua Voice - San Francisco | OnSite
Posted Jun 10, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- Not verified
- 401(k) match
- Not verified
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Market context
- U.S. role benchmark (BLS OEWS)
- $116,543 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +9.8% - Much faster than average
Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
- Company stage
- Growth-stage From the posting source checked Jun 20, 2026
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Staff Engineer San Francisco | OnSite ABOUT US Aqua Voice is building the voice input layer for the age of AI. We train our own models and build deep OS integrations because doing voice well requires controlling the entire stack. The way people work is changing. IC work is over; you manage AI agents now. This type of work is wonderfully suited for voice. We aren't building conversational agents. We believe the most natural way to interact with your computer is voice in text out (VITO). We believe that voice belongs at a level above the application, and that a small company can win by pushing the envelope. We are applying relentless energy to this opportunity and the results so far have been good. We hope you will join us. THE ROLE You will own technical systems across the stack. We're a small team, post-product-market-fit, and growing. We have real users and real problems. We prefer modern tools-Bun over Node, Fly over AWS when it makes sense, PyTorch over legacy ML frameworks. THE WORK GPU inference: We run our own ASR models. Real-time transcription: WebSocket state machines, multi-provider failover, sub-100ms latency targets. We track 30+ metrics per session. Native apps: Swift on macOS, C# on Windows, Electron IPC. System-level programming. Backend: Django for billing and analytics (oops). Celery for background jobs. PostgreSQL. There are no separate infrastructure and product teams. You will work on all of it. STACK - Languages: TypeScript, Python, Swift, C# - Runtime: Bun, Node.js, Django, FastAPI
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