Deepgram

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

Backend Engineer

• 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

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, Terraform

Engineer

• 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.

Audio Engineer

QA Engineer

• Model Evaluation Automation: Design, build, and maintain automated model evaluation pipelines that run against every candidate model before release. Implement objective and subjective quality metrics (WER, SER, MOS, latency/throughput) across STT, TTS, and STS product lines.
• Release Gate Integration: Embed model quality checkpoints into CI/CD and release pipelines. Define pass/fail criteria, build dashboards for model comparison, and own the go/no-go signal for model promotions to production.
• Agent & Model Evaluation Frameworks: Stand up and operate evaluation tooling (Coval, Braintrust, Blue Jay, custom harnesses) for end-to-end voice agent testing—covering accuracy, latency, turn-taking, and conversational quality and custom metrics across real-world scenarios.
• Active Learning & Data Ingestion Testing: Partner with the Active Learning team to validate data ingestion infrastructure, annotation pipelines, and retraining automation. Ensure data quality standards are met at every stage of the flywheel.
• Industry Benchmark Automation: Automate execution and reporting of industry-standard benchmarks (e.g., LibriSpeech, CommonVoice, internal production-traffic evals). Maintain reproducible benchmark environments and publish results for internal consumption.
• Language & Domain Validation: Build and maintain test suites for multi-language and domain-specific model validation. Design coverage matrices that ensure new languages and acoustic domains are systematically evaluated before GA.
• Retraining Automation Support: Validate the end-to-end retraining pipeline across all data sources—from data selection and preprocessing through training, evaluation, and promotion—ensuring automation reliability and correctness.
• Manual Test Feedback Loop: Design and operate human-in-the-loop evaluation workflows for subjective quality assessment. Build the tooling and processes that translate human feedback into actionable quality signals for the ML team.

Model Evaluation QA Lead

Developer Relations

• Ship Reference Patterns: Architect and open-source sample apps
• Code-First Content: Produce technical documentation
• The "Zero-Index" Sensor: Turn feedback into "Friction Reports"
• Scale Awareness: Author high quality technical content
• Technical Outreach: Engage where developers live (GitHub, X, Discord)
• Strategic Travel: Spend ~20% of time leading workshops and speaking at conferences

Staff Developer Advocate

Revenue Operations

• Support Quote-to-Cash processes, including:
• - Supporting CPQ workflows to ensure deals are configured and quoted correctly
• - Reviewing order forms and amendments for accuracy and compliance
• - Provisioning customer contracts, subscriptions, and usage entitlements into internal systems
• Support billing, invoicing, and monetization workflows in partnership with Finance
• Reconcile customer usage, billing, and revenue data across CRM, product, and finance systems
• Serve as a hands-on Salesforce administrator:
• - Build and maintain reports and dashboards
• - Support flows, automations, and system enhancements
• - Help maintain data quality and governance standards
• Triage, prioritize, and execute a wide range of RevOps requests
• Proactively identify inefficiencies and manual processes and help implement improvements
• Leverage AI tools and automation to increase operational efficiency
• Contribute to documentation and scalable RevOps processes as the company grows

Revenue Operations Analyst

Product Marketing

• Own onboarding for all GTM roles (Sales, SDR, CSM, etc.), designing and continuously improving a structured ramp program that accelerates time-to-productivity and ensures consistent execution.
• Build and run our continuous enablement engine, ensuring teams stay up-to-date on:
• - New product launches and features
• - Messaging and positioning updates
• - Competitive landscape and differentiation
• - Process, tooling, and playbook improvements
• Maximize the value of our AI and productivity tools, partnering with RevOps and Leadership to:
• - Drive adoption of enablement, CRM, and AI tools
• - Improve workflows and seller efficiency
• - Standardize best practices and usage patterns across the org
• - Continuously evaluate AI and enablement tools that reduce friction in how we work
• Build and run our ongoing enablement and certification programs, ensuring GTM teams stay current on product, messaging, competitive positioning, and core selling skills as the company evolves
• Create and maintain the GTM knowledge system, including:
• - Playbooks, battlecards, talk tracks, and internal documentation
• - Role-based enablement paths and certifications
• - A single source of truth for how we sell and win
• Lead enablement for major launches and initiatives, partnering with Product, Marketing, and Leadership to:
• - Translate product updates into sales-ready messaging and execution
• - Build training plans, materials, and reinforcement strategies
• - Translate strategy into field execution at scale
• Measure and prove enablement impact, by:
• - Defining success metrics (ramp time, win rates, productivity, adoption, etc.)
• - Continuously iterating programs based on performance data and field feedback
• - Treating enablement as a business lever, not just a training function

GTM Enablement Manager

Account Executive

• Hunting and deal origination: Proactively identify enterprise restaurant operators in an active or emerging buying cycle, create access to senior decision-makers, and generate qualified opportunities that you personally drive to close.
• Closing enterprise deals: Run and close complex, multi-stakeholder enterprise sales cycles with major restaurant brands.
• Deal leadership: Own the full deal process with discipline and urgency. This includes discovery, qualification, negotiation, procurement, and close.
• Executive trust: Build credibility with CXOs and senior operators as a calm, fair, business-first partner who understands their world.
• Relentless follow-through: Drive momentum, unblock stalled deals, and keep pressure on timelines without burning relationships.

Enterprise Account Executive, Restaurants

Technical Customer Success

• Act as a technical expert and strategic advisor to enterprise customers, engaging directly with developers, engineers, and executives to align business goals with technical solutions.
• Build, nurture, and sustain customer relationships across all personas interacting with Deepgram (from developers, program managers to CIOs, CTOs, and other C-level stakeholders).
• Conduct regular on-site visits with customers to partner closely, work hands-on to drive adoption, and actively embed Deepgram into their workflows. Frequent travel may be required.
• Own and manage the full customer lifecycle: onboarding, adoption, technical enablement, expansion, and advocacy.
• Focus on making Deepgram successful in the customer’s environment; ensuring products are integrated, enabled, and adopted effectively, applying best practices, reference architectures, and creative solutions to drive outcomes.
• Continuously operate in discovery mode, surfacing customer issues, deeply understanding their complexity and business impact, and translating them into actionable requirements for internal teams.
• Confidently run live product demos, guide architecture discussions, and troubleshoot L1-style issues, bridging the gap between technical support, solutions design, and commercial growth.
• Maintain a deep understanding of Deepgram APIs, integrations, and AI/ML technologies.
• Leverage AI to amplify your impact; be an expert in how Customer Success can apply AI to drive customer outcomes, surface insights, and improve internal systems.
• Proactively identify & scope opportunities for expansion (cross-sell, upsell, multi-product adoption), partnering with Sales.
• Develop and execute structured customer success plans that align business outcomes with Deepgram’s product capabilities.
• Proactively initiate and lead executive business reviews, joint planning sessions, and strategy workshops to stay ahead of risks, ensure alignment, and surface opportunities for growth.
• Serve as the voice of the customer internally, influencing product roadmap, GTM strategy, and even the internal tools and processes we build to support customers.
• Track, analyze, and report on key performance indicators (adoption, usage, health, satisfaction, expansion, and overall revenue impact).

Customer Success Engineer – APAC

IT Support

• Evaluate and implement centralized identity and access management tools (e.g., Okta, Google Workspace, JumpCloud) to simplify logins and strengthen security.
• Lead the rollout of a password manager and define policies for account access, permissions, and credentials.
• Oversee company hardware- ordering, setup, shipping, retrieval, and inventory tracking for new hires and departing employees.
• Serve as the primary point of contact for technical issues, troubleshooting, and user support to help teammates work without interruption.
• Own the technical side of onboarding and offboarding, ensuring systems access is granted and removed smoothly and securely.
• Support IT, WiFi, and AV setup for any physical offices or shared workspaces, maintaining reliable connectivity and hybrid collaboration tools.
• Maintain secure and stable network infrastructure, VPNs, and connectivity for both in-office and remote employees.
• Partner with Security and Operations teams to support SOC 2 readiness, incident response, security audits, penetration testing, and service endpoint protection; promote security and IT best practices across the company.
• Implement data backup, recovery, and retention processes aligned with business continuity and compliance needs.
• Manage relationships with IT vendors, software renewals, and licensing compliance.
• Track IT spend, forecast future needs, and recommend cost-efficient, scalable solutions.
• Create and maintain IT documentation, helpdesk, and training materials to empower teammates and reduce repetitive issues.
• Build systems and workflows that grow with the company, automating wherever possible to minimize manual work.
• Partner closely with People Ops, Security, and Engineering to ensure IT processes are integrated across the organization.

IT Manager

Product Analyst

• Own the analytics strategy for self-serve growth—design experiments, build measurement infrastructure, and drive insights that increase conversion from signup to first programmatic request
• Build robust, repeatable analytics pipelines and dashboards from the ground up using Superset and Heap Analytics
• Partner directly with product managers and designers to define success metrics, establish baselines, and instrument products correctly
• Design and analyze experiments across the developer journey, with deep understanding of API/SDK adoption patterns
• Collaborate with analytics partners in Marketing and Sales to connect product usage signals with acquisition, activation, and downstream sales outcomes, building a holistic view of the end-to-end PLG funnel
• Surface patterns in product usage across our growing portfolio to identify high-value use cases, customer segments, and where to double down on investment
• Serve as the analytical partner to Product leadership: synthesize insights across multiple products and use cases to identify patterns that inform longer-term product strategy and investment decisions
• Establish experimentation best practices and analytical rigor as the team scales PLG motions
• Translate complex findings into clear, actionable recommendations that shape product roadmap and investment decisions
• Build the analytics muscle for the team—creating frameworks and systems that enable PMs to self-serve insights while you focus on strategic analysis

Staff Product Analyst

Artificial Intelligence

• Deeply understand our customers business – even better than they do – and be an expert on Deepgram’s product offerings.
• Partner with our Sales, Product, and Engineering to scope, build, and ship AI agents that handle thousands of customer interactions a day.
• Serve as the primary point of contact for large enterprise stakeholders and ensure flawless delivery of complex AI solutions across enterprise deployments
• Monitor performance, adoption, and feedback from live deployments
• Translate field insights into actionable product requirements for eng/AI teams
• Help define and refine ROI metrics that drive large expansion deals

Enterprise AI Strategist, Restaurants

Full-stack Engineer

• 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 – Deepgram for Restaurants

Human Resources

• Serve as a primary point of contact for employee relations matters, including performance concerns, interpersonal issues, investigations, and complex workplace scenarios
• Coach managers through difficult conversations, feedback delivery, performance management, and documentation
• Provide consistent, fair, and legally sound guidance across key employee lifecycle moments
• Act as a trusted advisor to leaders on people-related risks, decisions, and trade-offs
• Partner with the Head of People to translate company strategy into people practices that are right-sized for scale
• Identify patterns and systemic issues early and recommend practical, upstream interventions
• Serve as a change partner to leaders, helping design, position, and operationalize organizational changes to drive understanding, adoption, and trust.
• Support performance management processes, goal-setting, feedback cycles, and manager capability building
• Partner with leaders on team structure, talent and succession planning, and ways of working that enable strong performance and sustainable growth
• Help managers navigate underperformance, role clarity challenges, and organizational change
• Reinforce a culture of high performance without unnecessary bureaucracy
• Help build and refine People processes, templates, documentation, and manager resources
• Partner on tools and workflows that improve consistency, efficiency, and employee experience
• Balance compliance, speed, and sound judgment as the company grows
• Partner with the Head of People to support change initiatives (e.g., policy updates, process shifts), including re-education, leader enablement, and reinforcement
• Partner with People Ops, Legal, and Finance to ensure compliance with federal, state, local, and our local partners with regard to international employment laws
• Support leave administration, policy application, and complex employee situations
• Help ensure People practices are defensible, consistent, and aligned with company values.