Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

As a Senior Machine Learning Research Engineer, you will research and implement advanced audio ML models, develop inference algorithms, and collaborate with the Operations team to enhance model quality.

Build and maintain production backend services and APIs to ingest, transform, and serve petabytes of audio. Own architecture, performance, observability, and debugging for distributed systems. Define internal service boundaries and collaborate with product, operations, and ML teams to iterate and ship research-driven audio features.

Lead design, build, and scale end-to-end audio data pipelines from prototype to production. Collaborate with researchers, engineers, and cross-functional teams to ensure high throughput, quality, and cost-efficiency, monitor pipeline health, and drive improvements using metrics.

Lead full-stack feature development, build scalable systems processing terabytes of audio, deploy and evaluate LLM/DSP solutions, drive research iteration for data collection, mentor engineers, and establish technical standards while shipping production-grade user experiences.

Build and ship full-stack features and scalable data-processing pipelines for terabytes of audio; deploy and evaluate LLM/DSP solutions; iterate quickly with researchers and operations to collect and surface high-quality audio dataset insights.

As a Product Engineer, you'll develop scalable full-stack features, build data processing pipelines, and collaborate with researchers to enhance audio data insights.

Lead the Product Engineering team in developing scalable systems and innovative products for audio data training. Responsibilities include full-stack development, deploying solutions, mentoring engineers, and maintaining technical standards.

The Senior Backend Engineer will design and maintain backend services, build scalable APIs, and optimize systems handling large audio data sets.

As a Deployment Strategist, you will partner with customers to shape audio AI strategies, leading projects from ideation to execution while fostering strong relationships. You'll work with technical teams to ensure high-quality outcomes and identify opportunities for implementation.

Own and scale David AI's global contributor network: acquire, activate, retain, and optimize contributors through experiments, product/incentive iteration, funnel optimization, and cross-functional partnership with Product, Operations, and Engineering.