About Inworld Inworld is a product-oriented research lab of top AI researchers and engineers, developing best-in-class realtime multimodal models and the only realtime orchestration platform optimized for thousands of queries per second.

We’ve raised more than $125M from Lightspeed, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta and Stanford, among others. Our technology has powered experiences from companies such as NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella and Bible Chat. We’ve also been recognized by CB Insights as one of the 100 most promising AI companies globally and have been named one of LinkedIn's Top 10 Startups in the USA.

Who We're Looking For

A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.

Experience We Find Useful

You don't need all of this. But you need enough to make a case.

• Foundation models: training, new architectures, RL, reward modeling, scaling
• Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis
• Frontier topics: multimodal models, agents, tool use, test-time compute, world models
• Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI
• PhD in ML/NLP — or equivalent practical experience you can point to
• Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions
• Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result

If you learned through building, competitions, or collaborations outside academia — that counts. We care about evidence, not credentials.

What We’re Not Looking For

• People who need a roadmap before they start walking
• Researchers who publish but never ship
• Engineers who ship but never question the approach
• Anyone whose best answer to "why?" is "the PM said so"

What Working Here Is Like

We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet " — and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.

We don't need a cover letter. A link to something you've built tells us more.

Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams.