Staff Full Stack Engineer - Build Scalable Audio Data

David AI Labs, Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Unlimited PTO

Health, dental, and vision coverage

401k access

Meals 2x daily through DoorDash

Job summary

David AI, the first audio data research company, is seeking a Staff Full Stack Engineer to lead our engineering team in building cutting-edge products that help customers harness audio data for model training.

You will own full-stack feature development, scale systems handling terabytes of speech data, deploy LLM- and DSP-based solutions, and mentor engineers as we ship production-ready experiences daily.

Qualifications

• 6+ years of product-focused full-stack engineering experience.
• Strong web development fundamentals and ability to build rapid prototypes.
• Proven track record delivering customer-focused engineering solutions.
• Experience in fast-paced environments with detail-oriented execution.
• Focus on intuitive, production-grade user experiences.
• Track record of success in technical leadership or engineering management.
• Willingness to learn AI/ML or audio concepts.

Responsibilities

• Lead full-stack feature development and iterate rapidly to deliver innovations to users daily.
• Build scalable systems processing terabytes of audio data and deriving insights.
• Deploy and evaluate LLM- and DSP-based solutions to enhance customer data understanding.
• Drive research iteration and interface deployment for data collection with researchers and Operations.
• Mentor engineers and establish technical standards as the team scales.
• Stay current with cutting-edge frameworks across software engineering, data engineering, ML, and signal processing.

Skills

Full-stack development

Leadership

Prototype to production

Web fundamentals

Job description

David AI, the first audio data research company, is seeking a Staff Full Stack Engineer to lead our engineering team in building cutting-edge products that help customers harness audio data for model training.

You will own full-stack feature development, scale systems handling terabytes of speech data, deploy LLM- and DSP-based solutions, and mentor engineers as we ship production-ready experiences daily.