David AI is the first audio data research company. We bring an R&D approach to data–developing datasets with the same rigor AI labs bring to models.
Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human—it fits naturally into everyday life. To unlock the full potential of AI, models need more—and better—audio data. That’s where David AI comes in.
David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we’ve brought on most FAANG companies and AI labs as customers. We recently raised a $25M Series A from Tier 1 investors like Jack Altman (Alt Capital), Amplify Partners, First Round Capital, Y Combinator, and more.
Our team is sharp, humble, ambitious, and tight-knit–we love spending time together. We’re looking for the best research, engineering, product and operations minds to join us on our mission to revolutionize audio AI.
As an Founding Applied ML Engineer at David AI you'll build cutting-edge speech and audio models, production inference systems and resilient pipelines that showcase what high-quality data can really do. You will:
- Research, design, and implement solutions using advanced signal processing algorithms and bleeding edge ML models with application to speech and audio.
- Develop production-grade inference algorithms, pipelines, and APIs with cross-functional teams that unlock key insights into our data for our customers.
- Collaborating with our Operations team to gather useful training and evaluation datasets to improve the quality of our models.
- Architect the systems that enable resilient, durable inference and evaluations.
- 5+ years of professional ML experience including DSP/ML audio algorithm development.
- Demonstrated experience owning ML pipelines end to end, from POC to production.
- Ability to translate research ideas or papers into high-quality Python code.
- Proficiency in Python and common Deep Learning frameworks like PyTorch.
- Ability to think broadly and cross-functionally about model quality in the context of user experience and the business value.
- Full autonomy to drive the ML roadmap, influence technical direction, and prioritize research and infrastructure investments.
- Experience working with a cloud technologies (eg. AWS or GCP) and developing machine learning models in a cloud environment.
- PhD or Masters in Computer Science or a related field.
- Experience training generative AI models.
- Expertise in audio signal processing both classical and machine learning techniques.
- Led ML teams, setting direction and driving development cadence.
- Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry.
- Competitive salary and equity package.
- Flexible PTO policy.
- Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans.
- Paid lunch and dinner in the office, every day through DoorDash.
- 401k access.