About David AI 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. Founded in 2024 by a team of former Scale AI engineers and operators, David AI has quickly gained traction, attracting most FAANG companies and AI labs as customers, and raising $5M from investors including First Round Capital, Y Combinator, and SV Angel. Our team is sharp, humble, ambitious, and tight-knit–we love spending time together. We’re seeking talented research, engineering, product, and operations professionals to join us in revolutionizing audio AI. Role and responsibilities As an Applied ML Engineer at David AI, you will build cutting-edge speech and audio models, develop production inference systems, and create resilient pipelines that demonstrate the power of high-quality data. Your responsibilities include: Research, design, and implement solutions using advanced signal processing algorithms and state-of-the-art ML models applied to speech and audio. Develop production-grade inference algorithms, pipelines, and APIs in collaboration with cross-functional teams to extract key insights from our data for our customers. Work with our Operations team to gather useful training and evaluation datasets to enhance our models. Architect systems that enable resilient, durable inference and evaluation processes. Who we’re looking for 5+ years of professional ML experience, including DSP/ML audio algorithm development. Proven experience owning end-to-end ML pipelines, from proof of concept to production deployment. Ability to translate research ideas or papers into high-quality Python code. Proficiency in Python and deep learning frameworks like PyTorch. Strong ability to think broadly and cross-functionally about model quality, user experience, and business impact. Full autonomy to drive the ML roadmap, influence technical direction, and prioritize research and infrastructure investments. Experience working with cloud technologies (e.g., AWS or GCP) and developing machine learning models in cloud environments. Bonus points if you have PhD or Master’s degree in Computer Science or a related field. Experience training generative AI models. Expertise in classical and machine learning techniques for audio signal processing. Experience leading ML teams, setting strategic direction, and driving development cycles. Compensation and benefits Rapid career growth opportunities at a fast-growing Series A company within a booming industry. Competitive salary and equity package. Flexible PTO policy. Comprehensive health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner daily through DoorDash. 401(k) plan access. #J-18808-Ljbffr
David AI