Jobs at Deepgram

Build and ship production backend services and AI-powered voice agent features. Own customer problems end to end, develop reusable agent modules, improve menu and catalog accuracy, contribute to model fine-tuning, run experiments, and integrate solutions into production. The role involves close customer collaboration, rapid experimentation, and working across Kotlin, Python, and TypeScript in an in-person San Francisco environment.

Research Engineer responsible for identifying weaknesses in voice AI models, defining improvement targets, designing evaluations, curating and generating data, fine-tuning deep learning models, and rapidly shipping production systems. The role emphasizes end-to-end ownership of customer problems, measurable production improvements, practical judgment, and fast experimentation. Candidates should have strong Python and PyTorch skills, production ML experience, and ideally experience with speech technologies, distributed training, publications, open source, or public benchmarks.

Research and improve voice AI models by identifying production weaknesses, defining evaluation metrics, curating data, fine-tuning deep learning systems, and rapidly shipping solutions. The role focuses on speech-to-text, text-to-speech, voice agents, model evaluation, customer-driven research, and production machine learning systems.

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.

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.

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.

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.

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.

Build and operate Deepgram’s deal desk, including approval matrices, pricing playbooks, credit and promotion guidelines, non-standard deal reviews, pricing analysis, Salesforce CPQ workflows, and audit-ready approvals. Partner with Sales, Customer Success, Product, and Finance on pricing, packaging, renewals, and revenue recognition. Use AI for first-pass deal reviews and continuously improve desk rules and processes.

Owns Deepgram’s North American events and field marketing portfolio, including 20+ trade shows, conferences, partner programs, executive events, roadshows, and account-based initiatives. Responsibilities include event strategy, budgeting, vendor and contract management, partner funding, brand activations, sales enablement, pipeline attribution, lead routing, ROI analysis, and post-event reporting. The role partners closely with Sales, Demand Generation, Product Marketing, alliances, and Marketing Operations, while developing AI-powered workflows and supporting the Deepgram Speak event series.

Owns marketing and go-to-market analytics, KPI definitions, attribution, campaign and sales-play measurement, scoring-model evaluation, dashboards, and weekly leadership reporting. The role reconciles Salesforce, HubSpot, and attribution data; partners with data teams on source-of-truth datasets; and builds AI-powered analytics agents, automated reporting, anomaly alerts, and data-quality processes to guide budget and pipeline decisions.

Lead technical sales for Deepgram’s Voice Agent platform, owning discovery, architecture, proofs of concept, technical evaluations, and customer production launches. Partner with account executives on enterprise deals, carry a growth quota, build demos and integrations, develop sales enablement, provide product feedback, and collaborate with telephony, contact center, and LLM partners. The role requires deep voice-agent expertise across telephony, orchestration, streaming pipelines, and speech and language models.

Supports and improves revenue operations systems and workflows, including quote-to-cash, CPQ, billing, subscriptions, Salesforce automation, data governance, forecasting, routing, quotas, and commissions. Partners with Finance, GTM Engineering, Sales, Customer Success, and Renewals to troubleshoot issues, reconcile data, automate repetitive processes, and improve commercial systems. The role also helps implement scalable processes and AI-enabled operational solutions.

Leads Deepgram’s GTM Engineering function, owning CRM, CPQ, forecasting, billing, data, integrations, automation, and internal tooling. Translates commercial needs into scalable systems and AI-powered workflows, establishes engineering standards, connects usage and revenue data, and partners with Product, Engineering, Finance, and Data teams. This player-coach role designs, codes, tests, ships production systems, and develops a small team while prioritizing automation and operational leverage.

Own Deepgram’s AI applications product line, including strategy, roadmap, customer definition, acquisition, activation, retention, monetization, and profitability. Lead zero-to-one product development, represent the product with customers and partners, and coordinate research, engineering, design, and marketing. Prototype and validate ideas through real usage and measurement while communicating decisions to executives. The role requires shipped, paid consumer or prosumer products, deep AI application experience, technical depth, design judgment, and strong product leadership.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.