Deepgram

Developer Relations

• Ship Reference Apps & Demos: Architect and open-source sample apps that solve real-world challenges — building real-time voice agents, orchestrating multiple voice AI models, streaming audio intelligence pipelines. Every demo should be runnable, well-documented, and designed for developers to learn from and build on.
• Code-First Content: Produce deep-dives, video walkthroughs, and "build-in-public" documentation that moves developers from idea to working prototype in minutes. You write and build for developers.
• Be the "Zero-Index" Sensor: Act as the first customer for every new feature and API change. Turn feedback from your own builds and from the developer community into Friction Reports that influence Product and Engineering priorities.
• Own Technical Narrative: Author high-quality technical content across blogs, social media, and video platforms that establishes Deepgram as the default choice for voice AI.
• Community Engagement: Engage where developers live (GitHub, Reddit, X, Discord, Hacker News) to represent Deepgram, answer questions, and earn community trust through consistent technical presence.
• In-Person Advocacy: Serve as Deepgram's on-the-ground presence primarily in the US. Lead workshops, speak at meetups and AI conferences, and build relationships with the developer community. Expect ~25% travel.
• Cross-Pillar Contributions: Contribute to the Developer Experience pillar - building integration recipes, improving SDK documentation, or building demo tooling.
• Multiply the Team: Document your processes and playbooks. Mentor teammates on content strategy, demo architecture, and community engagement patterns
• Connect Work to Outcomes: Frame your impact in terms of developer outcomes — sign-ups, activations, content-to-trial conversion, community growth. Articulate the business case and impact for your work.

Senior Developer Advocate

Vice President

• Own and deliver growth in self-serve revenue, contributing significantly to Deepgram's ARR targets
• Drive conversion rate of self-serve-led logos into enterprise contracts, working closely with Sales leadership
• Define, track, and optimize the full-funnel metrics that matter—from acquisition through activation, engagement, monetization, and expansion
• Establish quarterly and annual targets for self-serve growth and hold cross-functional teams accountable to shared KPIs
• Develop and execute a comprehensive PLG strategy across Deepgram's three product lines (STT, TTS, Voice Agents), each with distinct ICPs
• Design and optimize user journeys from website → signup → activation → usage → monetization, eliminating friction at each stage
• Build a high-velocity experimentation engine connecting hypothesis generation, execution, measurement, and learning
• Translate insights from data, user research, and market trends into actionable growth initiatives
• Build and lead the Self-Serve team, currently including a Senior Growth Product Manager and Product Analyst function, with plans to scale
• Provide strategic direction, coaching, and mentorship to develop world-class PLG and analytics talent
• Serve as the primary driver of alignment across Marketing, Product, Sales, Engineering, and Data teams for self-serve initiatives

VP, Self-Serve

Research Engineer

• Architect and manage horizontally scalable systems that dramatically accelerate the end-to-end training lifecycle for Speech-to-Text (STT) and Text-to-Speech (TTS) models.
• Design and implement internal UIs and tools that make ML systems and workflows accessible to non-technical stakeholders across the company.
• Oversee and manage training tooling, job orchestration, experiment tracking, and data storage.

Research Engineer – Machine Learning Systems

Backend Engineer

• Improve Deepgram’s core inference services including areas in networking, speech processing, audio transcoding, and latency and memory optimization
• Develop processes for measuring, building, and optimizing services to maximize system performance
• Debug complex system issues that include networking, scheduling, and high performance computing interactions
• Rapidly customize backend services to support our customer needs
• Partner with Product to design and implement new services, features, and/or products end to end

Backend Engineer – Inference Services

Engineering Manager

• Recruit, hire, train, and support top engineering talent to build a world-class team
• Transform cross-functional visions into detailed project plans, ensuring clarity across teams on commitments, risks, and timelines
• Define and own the technical strategy enabling acceleration of Deepgram’s ML training pipelines
• Promote a robust team engineering culture, including a focus on rigorous engineering standards as well as continuous improvement on team practices and processes
• Partner with DataOps and Research to design and implement new services, features, and/or products end to end
• Coach and mentor engineers to achieve high personal growth while delivering on ambitious team goals

Engineering Manager, Active Learning

Engineer

• Deploy Deepgram’s voice AI platform into complex restaurant environments
• Partner closely with customer leadership and technical stakeholders
• Write code, debug issues, and adapt the platform to real-world constraints
• Ensure enterprise deployments are technically flawless
• Monitor, troubleshoot, and resolve technical issues in live deployments
• Translate deployment challenges into actionable requirements for product and engineering teams

Forward Deployed Engineer, Deepgram for Restaurants

DevOps Engineer

• Architect and maintain our core computing platform using Kubernetes on AWS and on-premise, providing a stable, scalable environment for all applications and services.
• Develop and manage our entire infrastructure using Infrastructure-as-Code (IaC) principles with Terraform, ensuring our environments are reproducible, versioned, and automated.
• Design, build, and optimize our AI/ML job scheduling and orchestration systems, integrating Slurm with our Kubernetes clusters to efficiently manage GPU resources.
• Provision, manage, and maintain our on-premise bare metal server infrastructure for high-performance GPU computing.
• Implement and manage the platform's networking (CNI, service mesh) and storage (CSI, S3) solutions to support high-throughput, low-latency workloads across hybrid environments.
• Develop a comprehensive observability stack (monitoring, logging, tracing) to ensure platform health, and create automation for operational tasks, incident response, and performance tuning.
• Collaborate with AI researchers and ML engineers to understand their infrastructure needs and build the tools and workflows that accelerate their development cycle.
• Automate the life cycle of single-tenant, managed deployments

Site Reliability Engineer – AI & ML Infrastructure, Kubernetes, AWS, Terraform

General Counsel

• Structure, negotiate, and close enterprise sales and partnership agreements, along with a range of other commercial deals (including vendor and services agreements, data licenses, and marketing arrangements)
• Serve as a trusted partner to our sales and business development teams, helping them move faster and smarter
• Bring customer empathy to every negotiation, understanding the businesses we serve well enough to craft agreements that close faster and hold up longer
• Design and implement scalable legal processes — standardizing deal terms, building templates, and streamlining the path to signed agreement
• Provide clear, practical guidance on privacy, intellectual property, data security, and AI-specific legal issues as they arise
• Stay ahead of the evolving legal landscape for AI technologies and their impact on customers, translating developments into actionable guidance for our teams
• Roll up your sleeves on the full breadth of legal issues that come with being a fast-growing startup

Associate General Counsel

Social Media Manager

• Define Deepgram’s Social Strategy: Establish the role, tone, and social pillars for Deepgram across LinkedIn, X, and emerging channels. You’ll decide where we show up, what we create, and how we define success.
• Own the Social Calendar: Decide what we post, when we post, and maintain the company’s central social calendar. Ensure social is always in sync with our biggest launches, campaigns, and community milestones. Lead cross-team planning (Marketing, DevRel, Product) to keep the social calendar fresh and make the most of every opportunity.
• Develop the Content Engine: Drive social content creation from ideation to publishing. Concept and produce social-first series—specifically video-led formats—that demystify Voice AI and highlight innovative Deepgram use cases.
• Craft Compelling Copy: Write clear, sharp, and brand-aligned copy across all platforms. Partner with our executive team to amplify their voices.
• Engage the Community: Monitor cultural and industry conversations. You’ll facilitate authentic response to our online community, ensuring Deepgram is a meaningful participant in the AI discourse.
• Partner with Influential Voices: Identify and partner with influential voices, advocates, community members, and customers to tell the Deepgram story in new and unexpected ways.
• Set the Standard: Set high quality social standards and coach the wider team on social content creation. Recommend content formats, posting strategies, and engagement tactics to maximize reach and impact.
• Analyze & Iterate: Define success metrics that tie brand-building to business objectives. You’ll use performance data to refine our creative approach, not just report on it.

Senior Social Media Manager

Full-stack Engineer

• Work across the frontend with Kotlin (Android) and Swift (iOS)
• Build ui-components using SwiftUI and Jetpack Compose
• Design and integrate APIs using REST, supporting flexible, scalable data access across services
• Develop deep expertise in a few areas while remaining comfortable diving into new parts of the codebase
• Participate in code reviews and architecture discussions, fostering a culture of clarity, curiosity, and shared ownership
• Translate high-level product requirements into parallelizable, incrementally releasable tasks
• Balance short-term deliverables with long-term investments in efficiency, scalability, and performance

Senior Software Engineer – Mobile

• Design, develop, and maintain scalable, high-performance backend systems for our automated order-taking platform
• Collaborate closely with our team to ensure the seamless integration of our backend with our ML models and client devices
• Monitor and optimize the performance of our backend systems in production environments
• Build and maintain integrations with 3rd party restaurant software systems like POS, loyalty, payment gateways, and customer data platforms
• Implement best practices in system design, code quality, and testing to ensure a reliable, secure, and maintainable system
• Optimize AI pipeline to improve performance in challenging audio environments, robustly handle ambiguous customer requests, and rapidly scale to new menus
• Push the very boundaries of LLMs and voice AI technology to solve one of the technology industry’s historically elusive challenges
• Run experiments to validate the product impact of new functionality

Software Engineer, Voice Agents, AI

Technical Program Manager

• Own end-to-end delivery of new model versions and features for our flagship STT and TTS offerings, coordinating tightly across Research, Product, DataOps, and Engineering to hit milestones and ship on time
• Define and champion lightweight but effective processes that bring visibility and accountability to researchers’ daily workflows without adding unnecessary overhead or stifling scientific creativity
• Map dependencies and risks across all active cross-functional projects; maintain a clear picture of where things stand, where they’re at risk, and what needs to happen to keep execution on track
• Run cross-functional programs end-to-end: scope definition, timeline management, stakeholder communication, risk mitigation, and launch readiness
• Troubleshoot cross-team blockers quickly and build reliable partnerships across the technical organization so that handoffs between teams are smooth and accountability is clear
• Own proactive communication across all levels of the organization
• Respond quickly to shifting priorities, translating decisions made upstream into clear implications for timelines, team capacity, and cross-functional dependencies

Technical Program Manager, Research

• Improve Deepgram’s core inference services including areas in networking, speech processing, model orchestration, and observability
• Develop integrations with cutting edge in-house, third-party, and open-source AI models for perception and managing conversational dynamics
• Debug complex system issues that include networking, scheduling, and highly concurrent workloads
• Rapidly customize backend services to support our customer needs
• Partner with Product to design and implement new services, features, and/or products end to end

Backend Software Engineer – Engine Team, Voice Agent

Site Reliability Engineer – AI & ML Infrastructure, Kubernetes, Terraform

• Identify and correct audio artifacts, loudness inconsistencies, frequency imbalances, and sibilance issues across large-scale voice datasets.
• Design and implement scalable audio processing pipelines for voice data
• Define and implement scalable audio processing pipelines (EQ, compression, de-essing, dynamic range optimization) and normalization strategies across inter- and intra- voice recordings.
• Optimize audio quality across real and synthetic voices to ensure a consistent product experience across multiple use cases.
• Lead audio quality decisions during on-site voice actor recording sessions, including microphone selection, placement, gain staging, and environment setup.
• Define, document, and enforce audio quality standards for external vendors, including recording setup requirements, signal characteristics, and post-processing expectations, ensuring vendor-produced audio meets Deepgram’s training and product needs even when recordings are not done on-site.
• Convert expert-driven, manual audio workflows into automated, repeatable, code-based systems.
• Collaborate closely with research to improve training data quality, especially TTS speaker-specific fine-tuning.
• Contribute to synthetic data pipelines by defining and validating acoustic characteristics, guiding how different “sound profiles” should be produced and evaluated.