Responsibilities
- Own and ship one scoped project end-to-end during the internship, from design through reviewed and tested code running in staging or production.
- Land merged pull requests that improve an engineering component or product area such as the ASR pipeline, TTS latency, or developer SDKs.
- Make a measurable improvement that continues to provide value after the internship.
- Use AI tools to prototype, test, or debug more efficiently and share a workflow improvement with the team.
- Ramp up on Deepgram’s codebase and assigned domain sufficiently to debug and extend systems with decreasing supervision.
- Present the project and learnings to the team and leave documentation for future contributors.
- Work with a dedicated mentor through project milestones.
Requirements
- Have built projects, tools, scripts, or automations through coursework, personal work, or prior roles.
- Can read and write code in at least one programming language and learn new languages, tools, and codebases quickly.
- Use AI as a regular part of learning and building while applying human judgment appropriately.
- Reason from first principles and investigate the causes of failures.
- Can clearly explain technical work, tradeoffs, failures, and potential improvements.
- Currently pursuing a degree in computer science, engineering, or a related field, or developing equivalent skills through self-study, open source, or personal projects.
- Coursework or hands-on exposure to machine learning, distributed systems, audio or speech processing, or backend/web development is preferred.
- Projects or contributions involving AI/ML, real-time systems, or APIs are preferred.
- A prior internship, shipped project, or self-built AI-assisted workflow is preferred.
Categories
About Deepgram
Deepgram is the real-time API platform powering the trillion-dollar Voice AI economy. Backed by a $130M Series C at a $1.3B valuation, Deepgram is trusted by 200,000+ developers and 1,300+ organizations to build Voice AI products, platforms, and autonomous agents with the lowest latency, highest accuracy, and enterprise reliability. Our voice-native foundation models and runtime infrastructure have processed 50,000+ years of audio and over 1 trillion words, making Deepgram the most experienced voice AI platform in the world. Industry-leading models & platform: 👂 Nova-3 — the world’s most accurate real-time speech-to-text model 🔊 Aura-2 — professional, enterprise-grade text-to-speech 💬 Flux — the first Conversational Speech Recognition model designed to handle interruptions 🚀 Voice Agent API — enterprise-ready, real-time conversational AI 🧠 Saga — the Voice OS Beyond core infrastructure, Deepgram is expanding the Voice AI ecosystem through: 💪 Powered by Deepgram, supporting voice products built by leading AI startups and enterprise organizations 🌉 A new Voice AI Collaboration Hub in San Francisco for builders, partners, and the voice community 🍔 The acquisition of OfOne, delivering real-time Voice AI for restaurants and drive-thru operations with 95%+ containment 📃 A growing patent portfolio in Voice AI Much like APIs powered the payments and cloud economies, Deepgram is building the foundation for a trillion-dollar B2B Voice AI economy—centered on the most natural human interface: voice.