Find 14,000+ Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) Leads on GitHub

GitLeads monitors GitHub stars, forks, issues, and keyword signals to surface Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) leads who are actively building — right when they're most likely to buy your developer tool. Turn GitHub activity into pipeline.

Find Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) Leads Free →View Pricing
14,000+
Recommendation Engine Developer Leads indexed
14
GitHub signals tracked
73%
Avg email find rate
500+
New leads per day

Sample Recommendation Engine Developer Leads — Live from GitHub

Emails partially redacted. Sign up free to reveal contact details and start outreach.

DeveloperGitHub StarsReposLocationEmail
Alex Chen
@alexchen
Open source enthusiast. Building developer tools.
2,84034San Francisco, CAa***@gmail.comReveal →
Sarah K.
@sarahk_dev
Full-stack dev. Loves OSS and clean APIs.
1,19021Berlin, Germanys***@proton.meReveal →
Marcus T.
@marcust
Maintainer of several popular libraries.
3,47058Toronto, Canadam***@outlook.comReveal →
Priya R.
@priyaR
Engineer at a Series B SaaS startup.
89016Bangalore, Indiap***@gmail.comReveal →
Jordan M.
@jmdev
DevRel engineer. Writes about DX and tooling.
4,12047Austin, TXj***@hey.comReveal →
Unlock All 14,000+ Recommendation Engine Developer Leads — Free

How GitLeads Finds Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) Leads on GitHub

STEP 01

GitHub Signal Detection

We continuously index GitHub repositories tagged with Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers)-related topics. Stars, forks, new issues, and README keywords all fire signals.

STEP 02

Developer Profiling

Each developer's activity is scored by recency, influence (stars earned), and project relevance. You get leads ranked by likelihood to engage.

STEP 03

Contact Enrichment

We cross-reference public commit metadata, README contact sections, and linked social profiles to find verified email addresses.

STEP 04

Pipeline & CRM Export

Export leads to CSV, push to HubSpot, Salesforce, or Pipedrive, or use our REST API. Every lead includes GitHub context so your outreach is warm from the start.

Who Uses GitLeads for Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) GitHub Leads?

FAQ: GitHub Leads for Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers)

How many Recommendation Engine Developer Leads are on GitHub?

Our index currently tracks over 14,000 Recommendation Engine Developer Leads with verifiable activity in the last 90 days. GitHub hosts millions of developers; GitLeads filters to the ones who are actively building and most likely to be reachable.

How does GitLeads find Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) developer emails?

We extract emails from public commit metadata, README files, GitHub profiles, and linked social accounts. All data is publicly available and GDPR-compliant for B2B outreach under legitimate interest.

Can I filter Recommendation Engine Developer Leads by location, stars, or company?

Yes. GitLeads supports filtering by location (city, country), star count, follower count, company/org affiliation, repository topics, and activity recency. Build hyper-targeted lists in minutes.

How often is the Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) developer list updated?

Our GitHub crawler runs continuously. New developers who star or fork a Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) repository are added to your pipeline within 24 hours.

Start Finding Recommendation Engine & Personalization Developer Leads (LightFM collaborative filtering library contributors, RecBole recommendation system framework users, TensorFlow Recommenders model authors, surprise scikit-learn recommender contributors, session-based recommendation GNN engineers, A/B testing recommendation algorithm pipeline builders, vector similarity search infrastructure developers) Leads on GitHub Today

50 free leads every month. No credit card required. Export to CSV or push directly to your CRM.

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