David AI builds the data collection and evaluation systems that leading AI labs and FAANG companies use to continuously improve their voice models. We were founded in 2024 by former Scale AI engineers and operators, and we’ve raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other investors.
About Product EngineeringThe winning voice models will be built on the best systems for collecting human speech data and evaluating their models. Our challenge as engineers is to measurably improve our customers' models by building the most scalable and effective platforms for collecting speech data, verifying and refining its acoustic quality, and evaluating models.
You would build products with real users:
Tens of thousands of users take on work in our data collection platform and get paid for recording and transcribing audio, reviewing model outputs, and more.
Slingshot is where our operators run the business and decide what ships.
Data Marketplace is where customers search for and download research-grade datasets, and run and interact with private evaluations of pre-release models.
Every data product we sell runs through these surfaces: conversation data for speech-to-speech models, emotive speech for TTS, transcriptions for ASR, evaluations of public and private models, and more.
About the roleProduct quality shows up directly in our outputs. A confusing Babel flow produces bad recordings. A Slingshot view that buries a problem lets operators ship it to a customer. You will own features end to end, from the interface a contributor or operator sees to the service and pipeline behind it, and you will ship to production daily.
You will work closely with researchers, both in house and the labs'. We work with them to understand what to measure and which data to collect next, and we turn that into products that run at scale. When our researchers finds a new kind of data that could improve models, you build the recording flows and quality checks that turn it into something we can sell. Our ML team builds models that run inside these products, and you help take them to production.
We’re hiring product engineers across the stack and at varying levels of experience, and will place you on the team where your strengths fit best, whether that leans toward interfaces, backend systems or both.
In this role, you willShip features that thousands of contributors and operators use every day, across both the frontend and the APIs and services that power it.
Build scalable systems and data processing pipelines that turn petabytes of audio into usable quality signals.
Build, deploy and evaluate LLM and DSP based solutions that help customers understand nuanced features of our datasets.
Work with Research and Operations to quickly stand up new recording flows, quality checks and evaluations, and iterate on what they learn.
Keep up with new tools in software engineering, data engineering, machine learning and signal processing, and apply them where they improve the product.
5+ years of professional engineering experience in frontend, backend or full stack work.
Strong fundamentals in at least one side of the stack, and the curiosity to work across it.
Experience building both rapid prototypes and systems that scaled to many users.
A track record of delivering work that created value for customers.
Comfort in a fast environment where steady progress comes from careful execution.
A focus on intuitive, polished, production-grade products.
AI/ML or audio experience is not required.
Education or work experience in digital signal processing and a deep understanding of speech.
Experience building and deploying ML models in production, or building interfaces for ML-powered and data-heavy products.
Experience leading engineering teams (as a manager or tech lead) in a high-growth company.
Next.js, TypeScript, Node.js, PostgreSQL, AWS, Modal, WebRTC, FFmpeg
BenefitsUnlimited PTO.
Health, dental and vision coverage, with 100% coverage for most plans.
FSA and HSA access.
401k access.
Meals twice daily through DoorDash, plus snacks and beverages at the office.
Unlimited company-sponsored Barry's classes.
We sponsor international candidates across a range of visa types, including H-1B transfers, H-1B1, O-1, E-3, and TN, and we support STEM OPT. While we can’t guarantee any individual outcome, we’ve successfully sponsored teammates from all over the world.
Skills Required
- 2+ years of full-stack engineering experience
- Strong full-stack web development fundamentals and rapid prototyping experience
- Proven track record of delivering engineering solutions that provided customer value
- Experience working in a high-pace environment with detail-oriented execution
- Emphasis on building intuitive, polished production-grade products and user experiences
- Excitement to learn AI/ML and audio (experience not required)
- Educational or professional experience with digital signal processing and deep understanding of speech
- Experience building and deploying ML models in production
- Led or tech-led engineering teams in high-growth environments
David AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about David AI and has not been reviewed or approved by David AI.
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Fair & Transparent Compensation — Employer-posted ranges for engineering roles provide upfront visibility, and pay is often characterized as strong. This combination indicates broadly competitive cash compensation.
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Healthcare Strength — Medical, dental, and vision coverage is described as top‑notch with 100% employer-paid premiums for most plans. Such coverage depth signals strong core healthcare value.
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Wellbeing & Lifestyle Benefits — Twice-daily meals, office snacks, and unlimited company‑sponsored fitness classes are explicitly offered. These lifestyle perks enhance the overall package beyond core pay and insurance.
David AI Insights
What We Do
We're an audio data research company. Visit our website to learn more: https://www.withdavid.ai/


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