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

AI bootcamp (Berlin) - Accelerate AI with Google Cloud

13 February Online

Join this event

🎟️ Register / View Event Details

About this event

Important: Register on the event website is required for admission.(RSVP is turned off on meetup)

Description:
Join Google Cloud Labs for an immersive, hands on workshop learning how to build and scale production-grade AI agents with Cloud Run and GPU support.

This is a hands-on program designed to take your AI applications from prototype to full-scale production. In the world of AI development, a great idea is just the beginning. The real challenge lies in transforming that initial spark into a secure, scalable, and robust application that can handle real-world demands.

Get ready to get your hands dirty! This is an interactive session, not a lecture. Through a series of live labs, you'll tackle real-world challenges, from securing your services to deploying advanced AI agents. You will leave with practical skills and the confidence to take your own AI projects to the next level.

What You Will Learn:

Deploy Secure, Production-Ready Services: Master the essentials of securing your applications on Cloud Run. You will build and deploy a Model Context Protocol (MCP) server and learn to implement authentication to ensure that only authorized clients and agents can interact with your service.
Build Intelligent Agents: Dive into the Agent Development Kit (ADK) to construct an intelligent agent capable of understanding a goal and using tools to achieve it. You'll connect your agent to the secure MCP server you built, giving it the power to perform real-world tasks.
Containerize and Deploy: Take your working agent and prepare it for a consistent, portable deployment. This is a crucial step for managing applications in a serverless environment.
Harness the Power of GPUs on Cloud Run: Deploy your containerized agent to a Cloud Run instance and attach a GPU to accelerate your models. You will gain hands-on experience managing production configurations and testing a live, GPU-accelerated application.

Agenda

9:00AM - 9:30AM: Check-in, Networking, Coffee, and Breakfast
9:30AM - 10:00AM: Keynote: From AI Prototype to a Multi-Component Production App
10:00AM - 10:20AM: Tech Talk 1: The New Agentic Workflow: Empowering AI with Tools via MCP
10:20AM - 11:20AM: Lab 1: Deploy a Secure MCP Server on Cloud Run
11:20AM - 12:30PM: Lab 2: Use an MCP Server on Cloud Run with an ADK Agent
12:30PM - 1:30PM: Lunch Break
1:30PM - 2:10PM: Tech talk 2: From Agent to Application: Production Patterns for Scalable AI
2:10PM - 3:20PM: Lab 3: Deploying a Production-Grade Agent to Cloud Run with GPU
3:20PM - 3:30PM: Closing remarks & the path forward
3:30PM - 4:30PM: Q&A, Networking, and Happy Hour

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity