About the job
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About Zello
Zello is a premier voice-first communication platform that leverages our cutting-edge push-to-talk technology to enhance collaboration and productivity for desk-less workers. With over 175 million users globally, we proudly stand as the leading push-to-talk app worldwide, facilitating an astonishing 9 billion messages each month.
We are deeply committed to our core values, which guide our mission daily. We take pride in supporting frontline workers, connecting individuals during crisis situations around the world, and honoring our commitment to first responders.
And this is where you come in.
Zello's Data & AI team has successfully launched customer-facing AI features (such as the Ella assistant, AI Insights, message summaries, and AI-driven search) and is currently developing the internal AI infrastructure that will enhance the efficiency and effectiveness of all teams within the company. We are seeking an engineering intern who can tackle real operational challenges—such as support triage bottlenecks, manual data workflows, and fragmented internal knowledge—and create functional AI-powered tools. This is a hands-on role focused on building rather than merely observing or researching.
The Role
You will report to the Head of Data & AI, collaborating with the AI engineering team to design and implement internal productivity tools powered by LLMs, embeddings, and automation. The ideal candidate is someone who has independently built projects utilizing LLMs—not just because it was assigned, but out of genuine curiosity and a desire to see it come to fruition. You will have significant autonomy, real users, and tangible impact from your very first week.
After a Successful Internship, You Will Have:
Delivered at least two internal AI tools that are essential to Zello teams on a weekly basis—be it an automated triage agent, a CRM enrichment pipeline, an LLM-driven Slack workflow, or something entirely new.
Made substantial contributions to Zello's AI platform infrastructure—such as enhancements to embeddings pipelines, RAG systems, evaluation frameworks, or reusable components for future projects.
Dramatically reduced manual effort in at least one operational workflow, providing clear before-and-after metrics to demonstrate your impact.
Created comprehensive documentation that enables others to easily understand and build upon your work.

