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

Own Deepgram’s conversational design discipline for voice agents, including persona, turn-taking, interruption, repair, confirmation, pacing, and latency-aware behavior. Partner with ML and Engineering to ship conversational systems, establish quality evaluations and transcript review practices, and create reference agent experiences and developer guidance for the Voice Agent API. Define design principles, standards, and shared vocabulary while influencing technical partners without direct authority.

Leads Deepgram’s end-to-end Text-to-Speech research program, owning research strategy, technical direction, model development, evaluation, and production deployment. Advances neural audio modeling, prosody, expressiveness, multilingual generation, voice consistency, controllability, and inference performance. Builds and develops research teams, manages technical leaders, prioritizes experiments and compute, evaluates model quality, and partners with engineering and product leadership to ship production-grade models.

Lead Deepgram’s corporate legal function, including governance, IPO readiness, financings, M&A, employee equity, international subsidiaries, and regulatory developments. Partner with Finance, People, and company leadership to build scalable legal processes for a fast-growing AI company. Establish an AI-native legal practice while advising on a broad range of startup legal matters.

Own enterprise voice AI deployments for strategic restaurant customers, from technical discovery and architecture through integration, go-live, optimization, and production support. Write code, configure APIs and workflows, troubleshoot live issues, and collaborate with customer engineering teams and business leaders. Develop reusable deployment tools, reference architectures, and playbooks while translating field challenges into product improvements. Partner closely with Sales, Product, and Engineering and serve as a trusted technical escalation point.

As a Solutions Architect at Deepgram, you will engage with customers, solve technical issues, enhance support solutions, and develop automation processes.

Build and deploy production backend services, third-party integrations, internal tooling, and voice agents for strategic enterprise customers. Work directly on site with customer technical and business teams, monitoring and optimizing live systems for accuracy, latency, and throughput. Collaborate with research and product teams to extend the platform, provide field feedback, and create reusable solutions. The role involves regular customer-site work, solution scoping, technical problem-solving, and end-to-end ownership of deployed systems.

Own Deepgram’s end-to-end text-to-speech research program, including technical strategy, model architectures, experiments, training, evaluation, and production deployment. Lead researchers and technical managers, establish roadmaps, advance naturalness, expressiveness, multilingual generation, controllability, voice consistency, and inference efficiency, and partner with engineering and product leadership to ship high-quality models.

The Pre-Sales Solutions Engineer will engage in technical pre-sales activities, integrating AI solutions with customer needs, and facilitating technical sales processes.

Research Staff will develop foundational voice AI technologies, including low-bitrate neural audio codecs, steerable speech generation, disentangled audio representations, latent recombination, synthetic audio data generation, and multimodal speech-to-speech models. The role also involves designing scalable architectures, training methods, and inference algorithms optimized for hardware, billion-hour datasets, and real-time deployment. Candidates need strong mathematical foundations, foundation-model expertise, large-scale data pipeline experience, rigorous experimentation skills, deployment optimization knowledge, and publications or open-source contributions in speech or language AI.

Design, develop, and maintain scalable backend systems for automated order-taking platforms, collaborating with teams to integrate AI models and optimize performance across noisy environments.