World Models with DreamerV3 - AI Build & Learn
Event PAST

World Models with DreamerV3 - AI Build & Learn

04 September Online

About this event

Welcome to AI Build & Learn, a weekly AI engineering stream where we pick a new topic and learn by building together.

​This event kicks off a run on world models: models that learn an internal representation of how an environment works, then use it to predict what happens next and to plan. It's a natural next step after the generation and RL events, tying both threads together.

​We're starting with DreamerV3, a model-based RL agent and a great on-ramp to the idea. Dreamer learns a compact world model of its environment from experience, then trains its policy almost entirely inside imagined rollouts of that model rather than the real environment. It's lightweight (trains on a single GPU), works across many tasks with the same settings, and connects directly to the RL and MuJoCo work.

​Some things to look up to get started:
​Model:

​Background:

​​​Resources

​​In this stream

  • Intro to topic
  • ​​​​Community Discussion
  • Practical examples

​​​Community challenge (optional)
​​​Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.

​​​Note on Flyte / Union
​​​You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.

​​​Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 DevFound.ai. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals 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.

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.

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.

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.

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.

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.