Role Overview

Join the engineering team building voice-native foundation models and platforms that deliver real-time ASR, next-generation TTS, and LLM connectivity. As an intern, you will own a real project from design to production, contributing directly to the Deepgram codebase and exploring speech and audio ML and real-time systems.

Responsibilities

Design, build, and ship one scoped project end to end, from design through reviewed, tested code running in staging or production.
Contribute directly to a production codebase, including the core voice AI platform, Applied AI, or consumer wings.
Investigate voice AI, including speech and audio ML and real-time systems.
Utilize Agentic tooling (e.g., Claude Code, Codex) for prototyping, testing, and debugging.

Requirements

Proven track record of building projects, tools, scripts, or automations.
An AI-first approach to learning and building.
Ability to reason from first principles and troubleshoot root causes.
Proficiency in writing and reading code in at least one programming language.
Strong communication skills to explain technical work and architectural decisions.

Preferred Qualifications

Currently pursuing a degree in Computer Science, Engineering, or a related field.
Hands-on exposure to Machine Learning, real-time systems, or audio/speech processing.
Prior internship or hackathon experience involving AI-assisted workflows.

Skills

Machine Learning
Python
Speech Processing
Real-time Systems
LLMs