David AI Frontend Software Engineer at David AI builds intuitive, performant UI features for audio data analysis used by thousands of users. The role involves rapid iteration with researchers to enhance data collection interfaces.
Responsibilities
As a Frontend Engineer at David AI, you'll build cutting-edge, intuitive interfaces that help our users 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.
Ship polished, intuitive UI features that thousands of users will interact with daily.
Build performant, responsive interfaces on top of the data processing pipelines that derive actionable insights from terabytes of audio data every day.
Design and build interfaces that surface LLM and DSP based solutions, increasing our customers' understanding of nuanced features across our datasets.
Iterate rapidly on our research hypotheses by working closely with researchers and our Operations team to deploy interfaces to collect new data.
Stay up-to-date with cutting edge technologies and frameworks to apply to our current product offering across frontend engineering, design systems, and user experience.
Qualification
Some technologies we work withNext
Required
2+ years of frontend engineering experience.
Strong frontend fundamentals with experience creating rapid prototypes, as well as building interfaces that scaled to many users.
A proven track record of delivering engineering solutions that contributed value to customers.
Experience working in a high-pace environment where constant progress was enabled by detail-oriented execution.
Emphasis on building intuitive products and experiences that resonate with users, with a track record of shipping highly polished, production-grade interfaces.
AI/ML or audio experience is not required but you should be excited to learn.
Preferred
Educational or professional experience with digital signal processing and a deep understanding of speech.
Experience building interfaces for ML-powered or data-heavy products in a production environment.
Led (managed or tech-led) engineering teams in high-growth environments.
