Top Tech Jobs & Startup Jobs

Own and maintain deepgram.com end-to-end (Next.js front/back), Sanity CMS, component library, CI/CD, and QA. Lead i18n, technical SEO, AI/LLM discoverability, experimentation infrastructure, marketing integrations (GTM, GA4, HubSpot), and security audits while directing agency work and shipping high-velocity marketing site changes.

Drive inbound and outbound outreach to create sales opportunities with CTOs, VPs of Product, and CEOs; research speech-recognition use cases; collaborate with Partnerships, AEs, Sales Ops, and Sales Engineers to build pipeline and exceed quarterly targets.

Own the end-to-end product experience for AI coding agents integrating Deepgram: discovery, integration/onboarding, production use, verification, and feedback systems. Build measurement, experimentation, and optimization systems; define agent-specific developer platform requirements and prototype changes; turn agent traffic into rapid product improvements and run cross-functional execution.

As a Data Scientist at Deepgram, you'll tackle complex audio data challenges, develop scalable data pipelines, and collaborate with teams to advance voice AI technologies.

Lead complex deployments of Deepgram's Voice AI platform to federal customers, guiding technical discovery, solution design, and integration builds while ensuring successful implementations.

Lead end-to-end delivery of complex technical programs spanning hardware, software, and research. Define workstreams, set milestones, coordinate cross-functional teams, identify and mitigate risks, dive into technical details, and build lightweight processes and tooling to scale AI/ML infrastructure and GPU/cloud deployments.

Design and build scalable, automated evaluation pipelines and infrastructure to validate speech, audio, and multimodal models. Translate research benchmarks into enforceable pass/fail gates, run batch and streaming tests, operate canaries and continuous monitoring, integrate quality gates into CI/CD, and partner with research, training, inference, and infra teams to prevent regressions and ensure production model quality.

Lead end-to-end design and execution of voice data programs: build ingestion pipelines, labeling specs, tooling, and quality safeguards; align data strategy with research and product; manage vendors and teams; track throughput, quality, and vendor performance; and prototype/deploy data tools to scale datasets that improve speech and voice AI model outcomes.