Staff Full Stack Engineer

At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company.

We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models.

As a Staff Full Stack Engineer at David AI, you’ll lead our engineering team in building cutting-edge products that help our customers make sense of the audio data they’ll use to train their models, working closely with researchers to consistently iterate on how to best collect our data.

Lead full-stack feature development and iterate rapidly to deliver innovations to our users daily.

Build scalable systems processing terabytes of audio data and deriving actionable 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.

6+ years of product-focused full-stack engineering experience.

Strong web development fundamentals with experience building rapid prototypes and scalable user solutions.

Proven track record delivering engineering solutions that provide customer value.

Experience in fast-paced environments with detail-oriented execution.

Focus on building intuitive, highly polished production-grade user experiences.

Track record of success in technical leadership or engineering management.

AI/ML or audio experience is not required but willingness to learn is essential.

Educational or professional experience with digital signal processing and a deep understanding of speech.

Experience building and deploying ML models in a production environment.

Led (managed or tech-led) engineering teams in high-growth environments.

Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev , WebRTC, FFmpeg.