Jobs at Deepgram

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.

As a Software Engineer at Deepgram for Restaurants, you'll design and maintain scalable backend systems for automated ordering, integrating AI models, optimizing performance, and ensuring smooth interactions with restaurant software.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

The role involves researching and developing large language models (LLMs) with a focus on transformer architecture, data curation, distributed training, and optimization. Responsibilities include conducting experiments, collaborating with teams, and staying updated on deep learning advancements.

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.

Conduct talent mapping, market research, proactive sourcing, and pipeline development across technical, business, and leadership roles. Partner with recruiters and hiring managers to define target profiles, identify passive candidates, analyze talent availability and compensation trends, and deliver actionable market intelligence. Build evergreen talent communities, improve research workflows and tools, and adapt quickly to changing hiring priorities.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Own the company’s metric registry and canonical definitions, resolve conflicting metrics, enforce definitions in semantic and catalog systems, and retire redundant reporting assets. Build data quality checks, route failures to accountable owners, and evaluate AI agents against ground truth. Enable trustworthy self-service analytics through governed data. The role requires strong SQL, production ownership of a semantic or metrics layer, data catalog or lineage experience, clear documentation, and cross-functional decision-making.

Lead and coach a recruiting team while owning day-to-day talent acquisition execution across engineering, research, and go-to-market functions. Run full-cycle recruiting, support complex searches, build AI-assisted workflows and scalable recruiting systems, use funnel data to diagnose performance, develop recruiters, and improve hiring quality through structured interviewing and stakeholder coaching.

Partner with the SVP of Customer Success to improve executive effectiveness and organizational operating rigor. Responsibilities include calendar and meeting management, forecasting and business analytics, executive and board reporting, cross-functional initiative coordination, operating-rhythm management, action tracking, process improvement, and synthesizing data into insights, risks, decisions, and recommendations. The role combines executive support, business operations, project management, and analytical judgment.

Designs and maintains automated test frameworks and exploratory suites for products, APIs, SDKs, AI models, and data platforms. Develops functional, integration, end-to-end, regression, API, browser, load, and reliability tests; creates datasets, evaluation pipelines, dashboards, and CI/CD release gates. Partners across Engineering, Research, Product, Data, and Infrastructure to validate model behavior, data quality, performance, and production readiness. Documents reproducible defects, supports triage, and communicates risks.