Machine Learning Engineer ($175K – $250K + Equity) at Stanford-born AI governance startup

This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers.

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Job Title

Machine Learning Engineer: LLM Interpretability & Systems

Salary

$175K – $250K + 0.5% – 1% Equity

Company Description

Stanford-born AI governance startup backed by Gradient Ventures, General Catalyst, and Y Combinator

Job Description

You will operate deep within the model stack to build the deterministic governance layer for enterprise AI. By leveraging mechanistic interpretability, you'll work directly with model internals—weights and activations—to enforce policy and prevent drift. This role transforms frontier research into production systems that make LLMs reliable for Fortune 500 institutions.

Location

San Francisco, USA

Why this role is remarkable

• Work at the intersection of frontier AI research and production environments, moving beyond simple prompting to influence the mechanics of model cognition.
• Join a high-pedigree team born out of Stanford research, backed by elite investors including Google’s Gradient Ventures and Y Combinator.
• Drive massive impact by building the core "Policy Engine" that enables the world's most important institutions to deploy generative AI with confidence.

What You Will Do

• Implement techniques like activation patching and control vectors to achieve targeted, repeatable improvements in model output.
• Design and optimize feature-level intervention systems that enable deterministic policy enforcement at inference time for commercial and open-source models.
• Build the evaluation and deployment loops required to ship interpretability-based changes reliably into complex enterprise environments.

The ideal candidate

• Possesses a deep mathematical foundation in Transformer architectures and PyTorch internals, with experience training or fine-tuning models beyond superficial augmentation.
• Demonstrates the ability to translate academic papers on mechanistic interpretability into robust, production-ready code.
• Exhibits an ownership mindset and technical curiosity, driven to solve the challenge of making non-deterministic models auditable and controllable.

Who are Jack & Jill?

Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.

And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.

How does this work?

• Jack's an AI agent for job searching and career coaching. He works for you.
• Jill is the AI recruiter working for the company. She recruits from Jack's network.
• If it's a match and the company wants to meet you, they'll make the intro. In the meantime, if you'd like, Jack will send you excellent alternatives.

We never post fake jobs

This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network.

Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description.

We appreciate this can make them look a bit suspect, but there isn't much we can do about it.

Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.