About Inworld
Inworld is a research lab of top researchers and engineers, building the world’s top-ranked realtime voice models.
Today our models are the #1 ranked realtime voice models in the world. They are used to power the largest consumer-facing AI applications available, across categories like health, fitness, learning, therapy, companions, customer experience and media; representing 100s of millions of end users. Our work spans areas like research and development of state-of-the-art models, optimizing realtime inference, and creating best-in-class APIs and products that allow developers to engage their users.
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.
Who Thrives Here
Pathfinders: You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
Full-Cycle Researchers: You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output.
First-Principles Engineers: You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem.
Mission Owners: You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.
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.
For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements.
Skills Required
- PhD in ML/NLP or equivalent practical experience
- Experience with foundation models, training, new architectures, RL, reward modeling, scaling
- Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI
- Experience in full-stack research ownership
- Professional fluency in English (written and spoken)
What We Do
Inworld AI is a realtime voice AI research lab and platform. It builds the voice layer for consumer AI, the speech that powers companions, tutors, coaches, customer-service agents, and creative and content applications. Inworld's flagship product is text-to-speech, top-ranked on the independent Artificial Analysis Speech Arena, and around it the company offers a full realtime voice stack. That stack includes text-to-speech (Realtime TTS-2, with over 100 languages and natural-language voice steering), speech-to-text, and an LLM router that reaches 200+ models from every major provider with no markup. Developers can call any product on its own, for example Realtime TTS through a single API call, or combine speech-to-text, an LLM, and text-to-speech into one live conversation through the Realtime API. Dedicated GPUs are available for the largest workloads. Inworld serves developers and founders building consumer AI products. As voice quality becomes commoditized, the company's focus is realtime conversation at scale: voice agents that respond in roughly 200 milliseconds for thousands of simultaneous users, at a cost that stays efficient as usage grows. Inworld is a product-oriented research lab. Its founding team pioneered conversational AI and generative models at API.AI (acquired by Google and renamed Dialogflow), Google, and DeepMind, with expertise spanning language models, speech synthesis, multimodal interaction, and design. Inworld has raised more than $125M from investors including Lightspeed, Kleiner Perkins, Founders Fund, CRV, Intel Capital, BITKRAFT Ventures, Section 32, Meta, Microsoft's M12, and LG Technology Ventures. The company was one of six selected for the 2022 Disney Accelerator.
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