Machine Learning Intern/Graduate

About Filed

Filed is building the first AI tax preparer trusted by America’s accounting firms. This industry might seem boring—but it’s a $70B backbone of the economy that’s breaking under a talent shortage no one has solved. We’re fixing it—fast.

In just 9 months, we’ve hit strong product-market fit, are generating fast-growing, sticky revenue, and are backed by top-tier investors. We’re not a tool—we’re the missing workforce firms have been sounding the alarm for. We’re building the future with expanding our already 30 person team, with those who want to say “I was there when it all started.”

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Why this might be the worst internship/graduate role ever:

We move fast. Like, prototype-in-the-morning, ship-in-the-afternoon fast.

There’s no perfect dataset. You’ll build with ambiguity, ship without permission, and find that your code is in prod before your pull request gets a second emoji.

If you’re looking for hand-holding, safe tasks, or academic-style research, this isn’t the place.

But…

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Here’s why it might be the best decision of your early career:

You’ll own real systems—starting with our LLM evaluation pipeline. This isn’t a throwaway side project. It’s core infra for how we evaluate the AI that people trust with their taxes.

You’ll work across prompting, RAG, vector stores, and structured evals. You’ll experiment fast, learn faster, and get feedback from real users—yes, even as an intern.

If it works, we ship it. If it doesn’t, we fix it.

You’ll be part of every decision. And you’ll leave knowing what it takes to build production-grade ML that actually helps people.

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What you’ll do:

• Build and improve our internal LLM evaluation system
• Automate model assessments with real-world inputs and outputs
• Work with engineers and PMs to measure what matters, not just what’s easy
• Explore prompt strategies, finetuning, retrieval techniques, and more
• Help us simulate users with uncanny accuracy—and catch model failures before they happen

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You might be a fit if:

• You’ve played with OpenAI, Gemini, Claude, etc.—and shipped something with it
• You’ve built your own evals or tools to debug model behavior
• You write clean Python, and know your way around APIs and cloud infra
• You’re excited to move fast, learn even faster, and figure things out as you go
• You care about building things people use—not just clever ideas

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What we offer:

• High-impact work from day one
• Real ownership over a critical system
• Direct mentorship from world-class ML builders
• Paid internship, with the potential to go full-time
• A team that moves fast, builds boldly, and tells the truth

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The process:

• A quick intro call
• One in-person working session with the team
• Then we decide together if it’s the right fight

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This isn’t an internship for the faint of heart. But if you’re looking to build real ML that ships—this is the one.

Let’s go.