How Do I Find AI Teams That Need Evaluation and Training Data?

A GTM play for Revnu, for data labeling, evaluation and RLHF companies. An AI team hiring evaluation, post-training or ML data engineers is building the pipeline your data feeds. Revnu finds those job posts, reads what each team is building, and reaches the hiring lead by email and LinkedIn.

When an AI team posts a job for an evaluation engineer, a post-training engineer or an ML data engineer, it is building the machinery that consumes labeled data. The post says which tasks, which domains and how they measure quality. Revnu finds those posts, reads each one and reaches the person hiring with a pilot built for the work they described.

Why it works

Eval and post-training hires are a budget decision about data quality. The new hire's first months are spent finding data that works, and a vendor who already has a pilot set for their task saves that time. The job post gives you the task, the domain and the quality bar in the team's own words.

How to run it

Name the roles. Evaluation engineer, post-training engineer, RLHF researcher, ML data engineer, data operations lead, or a domain such as "code evals" or "medical data".
Find the postings. Revnu finds fresh postings at AI labs, AI startups and enterprise ML teams, each with its date.
Read each posting. Revnu notes the tasks, domains, languages and quality metrics the post names.
Find the buyer. The hiring manager or the research or data lead the role reports to, with a verified work email.
Write by email and LinkedIn. The email names the work in the post and offers a pilot batch on one of their tasks, ready before the hire starts. A LinkedIn connection request follows, then a follow-up with a sample.
Run it weekly. New postings every week mean new teams building data pipelines.

The prompt

Find AI companies and ML teams that posted a job for an evaluation engineer, post-training engineer or ML data engineer in the last 30 days. Read each posting and note the tasks, domains and quality metrics it names. Find the hiring manager or research lead and their work email. Write an email about the work in the post and offer a pilot [data type] batch on one of their tasks, then connect on LinkedIn three days later.

Try this in Revnu

Each lead keeps the job post on its Signals tab with its date and link. Your first sequence waits for your approval in Review.

Run it every week

Every Monday, find AI teams that posted eval, post-training or ML data jobs in the last week and add the ones that fit our buyer to the Eval Hiring campaign.

Set it up once as a workflow.

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Frequently Asked Questions

Which roles make the best signal?

Roles that consume labeled data: evaluation, post-training, RLHF, reward modeling and ML data engineering. A post that names a domain, such as code, law or chemistry, tells you which experts the team needs.

Who should the email go to?

The hiring manager or the lead the role reports to, because they own the data problem today. At a small AI company, the CTO or founder.

Can it find teams outside AI labs?

Yes. Enterprises building their own models post the same roles. Tell Revnu the industries you want, such as banks or insurers, and it searches there.

Can I combine hiring with funding or launches?

Yes. "Hiring eval engineers and raised a Series A or later in the last six months" is a short, warm list. Say every signal in one message.