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

AI in Production: Vectors in the Newsroom & Healthcare Challenges

Name: AI in Production: Vectors in the Newsroom & Healthcare Challenges
Start: 2026-06-30T17:00:00.000Z
Location: Skyscanner

Online

Join this event

🎟️ Register / View Event Details

About this event

GDG Cloud London is thrilled to be partnering with Skyscanner for a deep dive into the world of AI applications in Production.

This meet-up is a unique opportunity to connect with fellow AI enthusiasts, industry practitioners, and researchers in a dynamic and interactive setting. We are going to have some pizza and networking at the end!

Don't miss out, RSVP now!AGENDA

18:00 - Doors Open & Check-ins

18:30 - Welcome & Intro

18:40 - Ellen Muller - Vectors in the Newsroom: Building Smarter Image Search at the Guardian.
When a photo editor searches our image management system for "protest" at 6pm on a deadline, they can't afford to get zero results because the images were captioned "demonstration." Traditional keyword search has no way to know those mean the same thing - and for an archive with inconsistent metadata, that gap matters. This talk is about how we added semantic search to the Grid (the Guardian's open source image management system) using embeddings and vector similarity. We'll dig into how vector spaces let you encode meaning rather than just text, and the practical choices (and mistakes) involved in shipping this into a real production system.

19:15 - Bruno Ripa - Technical challenges of AI adoption in Healthcare
Deploying AI in healthcare requires solving a shifting equation: balancing high-fidelity clinical utility against rigorous data sovereignty mandates and punishing infrastructure costs. This talk breaks down how our company navigates this fluid landscape daily. We will cover where we use AI in our stack, how localised data compliance continuously reshapes our engineering choices, and the concrete technical hurdles we encounter along the way. Rather than showcasing a finalised architecture, we will focus on the ongoing design decisions and trade-offs required to keep our product secure, reliable, and compliant, all while aggressively optimising compute and operational costs—proving that surviving the mutating challenges of healthcare AI is a continuous process of lean execution.

20:00 - Pizza & Networking

Agenda

Speakers

Bruno Ripa - Dyad (Senior AI Engineer)

Ellen Muller - The Guardian (Software Engineer)

Hosted By

Amanda Cavallaro, GDG Organizer

I'm an Aikidoka, Developer Advocate, Software Developer, Google Developers Expert, Linkedin Learning Author and a Full Stack Web Development Specialist.

Saverio Terracciano, GDG Organizer

Stefano Le Pera, GDG Organizer

Lorenzo Turrino, GDG Organizer

Kubra Harmankaya, Android Developer

Partner

Skyscanner (https://skyscanner.net/)

Complete your event RSVP here: https://gdg.community.dev/events/details/google-gdg-cloud-london-presents-ai-in-production-vectors-in-the-newsroom-amp-healthcare-challenges/.

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity