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Design and implement scalable, secure inference services for speech processing. Optimize networking, audio transcoding, latency, memory, and distributed compute orchestration. Debug complex system issues, customize backend services for customers, and partner with Product to deliver end-to-end features.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

The Staff Product Designer will innovate design systems and frameworks for AI-driven products, mentor designers, and enhance end-to-end design quality across various surfaces.

The FP&A Manager will lead revenue forecasting, support Go-To-Market strategies, utilize AI tools for efficiency, and drive performance insights across Sales and Marketing.

Own end-to-end renewal negotiations for strategic, high-value consumption-based accounts. Forecast usage-driven renewals, build pricing and packaging, defend value with data, identify expansion opportunities, and quarterback cross-functional deal strategy to prevent churn and capture growth.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

Take Deepgram's speech models and optimize, compile, and run them on resource-constrained embedded and edge hardware. Work across model compression, runtime performance (C/C++/Rust), RTOS/bare-metal and embedded Linux environments, vendor NPUs/DSPs and inference runtimes, benchmarking, deployment pipelines, OTA updates, and partner with silicon vendors to enable real-time, low-power on-device voice experiences.

Lead Deepgram's demand-generation function end-to-end: set strategy, build an AI-native repeatable demand system, run integrated performance campaigns (paid, web, events, field), partner with Sales and RevOps to convert leads to revenue, hire and grow a high-performing team, and establish attribution and reporting that ties spend to pipeline and revenue.

Lead design and delivery of an agent-based Intelligence Layer that autonomously analyzes product, usage, and revenue data. Build AI-augmented workflows, define semantic/data contracts, leverage voice models to extract insights from audio, advise CEO/Board on unit economics and NRR, and hire a small elite analytics engineering team.

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.