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AI candidate sourcing

Describe who you need. Pin finds them in 850M+ profiles.

AI candidate sourcing that starts from a job title, not a Boolean string. Pin builds the criteria, searches every profile worth searching, and tells you why each person fits.

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Try a search:

Senior AI engineer in NYC who has shipped LLM products. Hybrid is fine. No crypto.

Criteria Pin built

AI Engineer New York, hybrid 5–8 years LLMs AI agents Crypto

Matches 214 found · ranked by fit

  • Maya ChenSenior ML Engineer · Parallel Labs

    Yes, Six years shipping LLM products, two AI agents in production.

  • Priya RamanAI Engineer · Searchlight

    Yes, Built AI search at a Series B startup.

  • Daniel OkaforML Infrastructure Lead · Kinetic Robotics

    Maybe, Deep ML infrastructure, newer to LLM applications.

Illustrative example

Brief

Start with a title. Pin fills in the blanks.

Give Pin a role and a company. It researches the company, drafts the profile, and asks the questions a great sourcer would ask.

Have a JD? Paste it, upload it, or import it from your ATS.

Hi Alex, I can help you build the search for your Senior AI Engineer at ByteLogic. Do you already have a job description I should work from?

Not yet. Just the title for now.

No problem. I looked up ByteLogic: Series C, NYC HQ, building AI agents for customer support. A few quick questions to sharpen the search.

What seniority are you targeting?

Select all that apply

2 of 4
Tell Pin what you need…
Ask Pin to add or change any criteria
AI Engineer New York, hybrid 5–8 years of experience LLMs AI agents Python Evals Crypto Criteria

ByteLogic

AI · Series C · 400 employees · New York

Match

850M+ profiles. Only the ones that fit.

Pin reads every profile the way you would: trajectory, skills, the companies they've built at. Then it tells you why each person matches.

Approve the ones you like, pass on the rest. Need the hiring manager's eyes? Send them a review link.

Try it: approve or decline

Maya Chen

Brooklyn, NY

10FIT SCORE
Criteria

Shipped LLM products? Yes, six years shipping them, two AI agents in production.

Leadership? Yes, tech lead for 4 engineers, ready for a staff-track role.

LLMs & agents – Launched the AI agents behind Parallel Labs' support product.

Python – Python daily; owns the team's eval pipeline.

5–8 years – 6 years of experience.

Current

PSenior ML Engineer at Parallel Labs

Past

HSoftware Engineer at Helio

CBackend Engineer at Cartwheel

Education

CB.S. Computer Science at Cornell

Daniel Okafor

New York, NY

9FIT SCORE
Criteria

Shipped LLM products? Maybe, deep ML infrastructure, newer to LLM applications.

Startup pace? Yes, early engineer at a robotics startup.

LLMs & agents – Built model serving for Kinetic's vision models.

Python – Python and CUDA in production.

5–8 years – 8 years of experience.

Current

KML Infrastructure Lead at Kinetic Robotics

Past

OSenior Engineer at Orbit Systems

LSoftware Engineer at Lumen Labs

Education

NM.S. Computer Science at NYU

Priya Raman

Jersey City, NJ

8FIT SCORE
Criteria

Shipped LLM products? Yes, built AI search at Searchlight, a Series B startup.

Leadership? Maybe, mentors two engineers, no formal lead role yet.

LLMs & agents – Built retrieval and ranking for AI search.

Python – Python services behind Searchlight's search API.

5–8 years – 5 years of experience.

Current

SAI Engineer at Searchlight

Past

FSoftware Engineer at Fieldstone

BData Analyst at Brightwave

Education

GB.S. Computer Science at Georgia Tech

Approved 11

  • Sofia Alvarez9
  • Tom Becker10

Request review

Send

jordan@bytelogic.com

Reviewer can approve or decline shortlisted candidates for 48 hours.

Jordan approved 3 of 4

Boolean vs. plain English

Stop writing search strings that look like code.

The average LinkedIn Recruiter Boolean string is 180 characters and still misses the right people. Describe who you want instead.

Boolean string

("AI engineer" OR "ML engineer" OR "machine learning engineer" OR "applied scientist") AND (LLM OR "large language model" OR GPT OR "AI agent" OR RAG) AND ("new york" OR NYC OR brooklyn OR hybrid) NOT (crypto OR web3 OR blockchain) NOT (intern OR junior)

  • Misses “Member of Technical Staff” and other odd titles
  • Can't tell someone who shipped LLM products from a keyword mention
  • Returns an unranked list to read one by one

Pin

Senior AI engineer in NYC who has shipped LLM products. Hybrid is fine. No crypto.

  • Reads titles by what people actually do
  • Weighs real LLM work, not mentions
  • Ranks by fit and explains every match

Six things Pin sees that a keyword search can't.

Boolean search works on strings. Pin reads careers: the shape of someone's trajectory, the companies they chose, the work they shipped.

  • Skills over titles

    Pin reads what people have actually done. Titles vary across companies; skills and trajectories don't.

  • Multi-source coverage

    One search covers LinkedIn, GitHub, Crunchbase, Kaggle and more, deduplicated into a single shortlist.

  • Passive talent included

    Most of the 850M+ profiles belong to people who aren't applying anywhere. Pin finds them and Outreach reaches them.

  • Every match explained

    Each candidate comes with evaluation rows, Yes, Maybe or No, so you can see the reasoning before you approve.

  • Criteria you can steer

    Pin a must-have, ban a deal-breaker, or ask in plain English: “avoid consultancies”, “must have shipped at Series B+”.

  • Learns your bar

    Every approve and decline sharpens the next batch. The shortlist gets closer to your taste as you go.

AI sourcing vs. traditional sourcing tools.

Traditional sourcing is one sourcer, one platform, one query at a time. Pin runs the whole search for you.

PinBoolean searchLinkedIn Recruiter
Search method Plain English or just a job title Boolean strings Boolean + filters
Candidate database 850M+, multi-source Varies by platform LinkedIn only
Matching approach Skills-based hiring AI Keyword matching Keyword + title matching
Results Ranked by fit, with reasons Alphabetical or by date Relevance score
Time to shortlist Minutes Hours Hours
Niche roles Finds non-obvious matches Misses title mismatches Limited to LinkedIn profiles

Recruiters who stopped writing Boolean

Read more reviews on G2.

“Pin has supercharged our sourcing, helping our team build more top of funnel efficiently.”
Nick PatrickCEO & Co-founder at Radar
“It finds candidates that don't appear on L*nkedIn Recruiter.”
Ryan LevyManaging Partner at Cruit Group
“Pin makes sourcing candidates so natural and I love how you can just talk to it like it's a recruiter on your team and it goes hunting. By far our favorite new technology in a long time.”
Josh VolinskyCo-Founder at Synergy Search

AI sourcing questions

Plans from $100/mo.
Free plan, no credit card. See pricing

How does AI candidate sourcing differ from Boolean search?

Boolean search makes you build exact keyword strings and combine operators by hand. With Pin, you describe the person you want in plain English, or just give a job title and company. Pin turns that into criteria, evaluates candidates on skills and experience rather than keyword matches, and explains why each one fits. It finds people Boolean misses, especially for niche roles where titles vary across companies.

How many profiles can Pin search?

Pin searches 850M+ profiles across multiple sources, with 100% coverage of North America and Europe. It isn't limited to a single network like LinkedIn.

What is skills-based hiring AI?

Skills-based hiring AI evaluates candidates on demonstrated skills, experience patterns and potential rather than job-title keywords. A "Software Engineer III" at one company and a "Senior Developer" at another are correctly treated as equivalent, something keyword-based sourcing tools miss.

Do I need a job description to start?

No. Give Pin a role and a company. It researches the company, drafts the criteria, and asks clarifying questions about seniority, must-haves, location and deal-breakers. If you have a JD, paste it, upload it, or import it from your ATS.

Can my hiring manager review candidates?

Yes. Send a review link to the hiring manager or anyone on the team. They can approve or decline shortlisted candidates without creating a Pin account.

How fast does AI sourcing return results?

A search typically returns a ranked shortlist within minutes. Pin customers report a 5-day average time-to-candidate from initial search to scheduled interview.

What does AI candidate sourcing cost?

AI sourcing is included in every plan, from $100/mo. All paid plans include unlimited searches and job positions. Contact lookup credits (for revealing email and phone) start at 500/month. There's also a Free plan, no credit card needed.

Keep reading

Your next shortlist is one sentence away.

Give Pin a job title and see who it finds in 850M+ profiles, with the reasons each person fits.

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Free plan · No credit card