How does DevFound's AI job matching work?

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

Is AI job searching better than traditional methods?

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

What skills are needed for AI and ML jobs?

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

How do I get matched with AI jobs faster?

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

What locations have the most AI job opportunities?

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

Can DevFound's AI help with remote AI jobs?

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

devfound

Try for free

Event PAST

[Online] The Internet Archive for Data Scientists

20 January Online

Join this event

🎟️ Register / View Event Details

About this event

With a mission of "Universal Access to All Knowledge", the Internet
Archive is building a digital library of Internet sites and other
cultural artifacts in digital form for the last 29 years.

In this talk, core infrastructure engineer Pablo Duboue will walk us
through the project and its external APIs, which he helps
maintain. As a former data scientist himself, Pablo will discuss how the
different APIs can be useful for data scientists.

Outline
By the end of this session, participants will be able to:

The Internet Archive Project: history, core infrastructure engineering, the Wayback Machine, Open Library, digitization centres.
Using the IA through the Website: creating accounts, uploading material, derivatives, collections.
Using the IA through the Python `ia` Tool: instalation, IA APIs, IA and crawlers.
Contributing to the IA: uploading your own models / data, volunteering, copyright reform, donations

----------------------------------------
How to Join the Webinar
----------------------------------------
You can join via your browser (no app download required). Use Chrome or Firefox. Pre-register for the webinar:
https://www.bigmarker.com/neo4j/Data-Umbrella-Webinar

--------------------------------
Video Recording
--------------------------------
This event will be recorded and placed on our YouTube. We usually have it up within 24 hours of the event. Subscribe to our YT and set your notifications: https://www.youtube.com/c/DataUmbrella/

----------------------------------------
Time
----------------------------------------
20:00 UTC, 12pm PT / 3pm ET / 9pm Paris / 11pm EAT
----------------------------------------
About the Speaker
----------------------------------------
Pablo Duboue is a Core Infrastructure Engineer at the Internet Archive, contributing to site reliability and maintaining the legacy codebase that powers the platform (approximately 330,000 lines of PHP). Before joining the Internet Archive, Pablo had a 25 year career in applied language technologies and natural language generation, including earning a Ph.D. in Computer Science from Columbia University and joining the IBM TJ Watson Research Centre as a Research Staff Member.

LinkedIn: https://www.linkedin.com/in/pabloduboue/
GitHub: https://github.com/DrDub
Mastodon: https://mastodon.archive.org/@drdub

----------------------------------------
Connect with Data Umbrella
----------------------------------------
We invite you to follow Data Umbrella on our social networking sites to keep up to date on the latest news.

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity