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Open nowPosted 4 hours agoWe saw it 104 min after it went up

Growth Lead

Clera289 open roles

Where
San Francisco
Work mode
On site
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Your applicationOpen nowGrowth LeadClera · San Francisco

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Clera's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

8.4% of postings close within 7 days. Measured by our own scanner across the market. Clera postings stay open a median of 5 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 8.4%7 days
  4. 15.4%14 days
  5. 34.1%30 days
This job: posted 4 hours ago

Clera median: 5 days open

The posting

ABOUT THE ROLE

Join an early-stage AI infrastructure team to build relationships across the frontier AI ecosystem and help shape how the company tells its story. This cross-functional role brings together recruiting, culture, community, events, content, and go-to-market support.

WHAT YOU'LL DO

- Communicate the company's vision and create clear, engaging stories about its work.

- Find and connect with candidates, AI engineers, researchers, and other people across technical communities.

- Define company culture and values, screen candidates, and develop onboarding for new hires.

- Own end-to-end recruiting with the Chief of Staff, including improving systems, tools, and automated workflows.

- Partner with the marketing and events team to host community events, attend industry events, and create content.

- Work with go-to-market engineers to identify introductions and connection paths to priority leads.

WHAT WE'RE LOOKING FOR

- Three to eight years of relevant experience, with a background in recruiting, community, content, go-to-market, or early-stage startup operations.

- Experience owning recruiting processes and systems at an early-stage company, including recruiting operations, tools, and workflows.

- Experience connecting with people in technical communities and building relationships with key individuals.

- Ability to understand and clearly explain technical products related to frontier AI agents, reinforcement learning, and training data.

- Experience defining culture and values, creating onboarding processes, producing marketing or community content, and supporting events.

- An established network in reinforcement learning research, engineering, or startup communities, plus professional writing samples.

- Strong interpersonal skills, independence, and comfort working in a fast-moving environment with evolving responsibilities.

COMPENSATION & BENEFITS

Salary range: $130,000 to $225,000 annually. Visa sponsorship is available.

LOCATION

On-site in San Francisco, California, United States.

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One press. We do the rest.

  1. A CV for this posting

    Written against Clera's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Clera's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Clera's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

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  6. The interview in your calendar

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    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

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