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How to Actually Get Hired
Who reads applications, which channel gets a reply, and what they screen for.
Don't make these mistakes
Positioning yourself as a generalist ML engineer. They want deep expertise in interpretability or adjacent areas. This is a research lab, not a product company.
What gets their attention
The open–source entry point: Goodfire has open–sourced its Sparse Autoencoder interpreters. The best non–application path into the company is to fork the repo, run experiments on your own models, and share your findings publicly on the Alignment Forum, arXiv, or X. This is exactly how Goodfire's own team built their reputations, and Eric monitors this community directly. A well–written public post that uses Goodfire's tools and cites their papers is worth more than a cold email. The community shortcut: The mechanistic interpretability research community is small and tight–knit. The key gathering point is the MATS (ML Alignment Theory Scholars) programme – several Goodfire researchers went through it or supervise it. Attending MATS, applying for ARENA (the AI safety training programme), or engaging with Neel Nanda's TransformerLens community puts you in direct contact with the researchers who hired the Goodfire team. The B Capital signal: The Series B was led by B Capital with Eric Schmidt and Salesforce Ventures joining. Salesforce Ventures specifically signals that enterprise CRM and workflow AI is a target market for Ember. If you have Salesforce ecosystem experience combined with any ML background, that combination is unusual and directly relevant to an underserved hiring need. The employee to find: Search LinkedIn for 'Goodfire' and look specifically for researchers who transitioned from Anthropic's interpretability team or from MATS cohorts. These individuals are the natural referral network, engaging with their published work before requesting a referral is the warmest path in.
Why applying the normal way doesn't work
Goodfire uses an ATS, but referrals still come first. Cold applications aren't ignored — they're just behind referrals, sourced candidates, and recruiter picks.
Who to contact at Goodfire
We're still mapping Goodfire's hiring process. At this size ( people, AI), the hiring manager typically decides, but we haven't confirmed it yet.
What Goodfire screens for
What they look for: The open–source entry point: Goodfire has open–sourced its Sparse Autoencoder interpreters. The best non–application path into the company is to fork the repo, run experiments on your own models, and share your findings publicly on the Alignment Forum, arXiv, or X. This is exactly how Goodfire's own team built their reputations, and Eric monitors this community directly. A well–written public post that uses Goodfire's tools and cites their papers is worth more than a cold email. The community shortcut: The mechanistic interpretability research community is small and tight–knit. The key gathering point is the MATS (ML Alignment Theory Scholars) programme – several Goodfire researchers went through it or supervise it. Attending MATS, applying for ARENA (the AI safety training programme), or engaging with Neel Nanda's TransformerLens community puts you in direct contact with the researchers who hired the Goodfire team. The B Capital signal: The Series B was led by B Capital with Eric Schmidt and Salesforce Ventures joining. Salesforce Ventures specifically signals that enterprise CRM and workflow AI is a target market for Ember. If you have Salesforce ecosystem experience combined with any ML background, that combination is unusual and directly relevant to an underserved hiring need. The employee to find: Search LinkedIn for 'Goodfire' and look specifically for researchers who transitioned from Anthropic's interpretability team or from MATS cohorts. These individuals are the natural referral network, engaging with their published work before requesting a referral is the warmest path in.
Tailor your CV to the specific Goodfire role rather than sending a general one. Applications that mirror the language of the job description clear automated filters at a materially higher rate.
Mistakes that kill applications
Don't send the same CV you sent everywhere else. At people it's obvious, and it's the fastest rejection there is.
Lead with their problem, not your ambition. Goodfire is focused on The history of engineering is a history of fields that were transformed when practitioners stopped treating their medium as a black box and started understanding it from first principles — show you understand that.
Most AI applications get ghosted. A day-five follow-up can double your response rate.
Frequently asked questions
How do I apply to Goodfire?
Through the roles on our Goodfire jobs page, or directly to the hiring manager if you can reach them. At null people, direct outreach outperforms the form.
Does Goodfire respond to cold emails?
We haven't verified response rates at Goodfire yet.
Who is the hiring manager at Goodfire?
At this size, hiring is usually run by the hiring manager.
How competitive is it to get hired at Goodfire?
Roles at -person AI companies typically draw 100-250 applicants in the first two weeks. Applying inside 72 hours of a posting going live is the single biggest lever you control.
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