About ElevenLabs
ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always.
We have expanded from voice into three main platforms:
- ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.
- ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.
- ElevenAPI gives developers access to our leading AI audio foundational models.
Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders.
How we work
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High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.
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Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.
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AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.
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Excellence everywhere: Everything we do should match the quality of our AI models.
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Global team: We prioritize your talent, not your location.
What you’ll do
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Build safety systems: Design, develop, and scale automated moderation systems, abuse detection capabilities, and guardrails for AI agents across ElevenLabs’ products.
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Respond to emerging threats: Partner closely with the Investigations team to identify emerging abuse patterns, understand evolving threats, and continuously improve existing safety systems, detection mechanisms, and guardrails to address new risks.
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Own production infrastructure: Build and maintain a growing ecosystem of internal safety services, taking ownership of their architecture, deployment, reliability, monitoring, and ongoing operation.
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Bring ML models into production: Partner closely with ML engineers to deploy and integrate fine-tuned and proprietary ML models into production safety systems, ensuring they operate reliably and efficiently at scale.
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Build end-to-end solutions: Develop backend services, APIs, internal tools, and user-facing interfaces that enable effective moderation, safety operations, and policy enforcement.
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Collaborate across teams: Work closely with Product, Legal, and Safety Policy teams to translate business, regulatory, and policy requirements into scalable engineering solutions.
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Product: Understand and navigate the tradeoffs between product growth, user experience, and platform safety.
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Legal: Translate legal and regulatory requirements into practical, scalable safety systems.
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Safety Policy: Collaborate on how safety policies are implemented technically, while helping inform policy decisions through an understanding of engineering capabilities and constraints.
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Shape our technical direction: Contribute to architectural decisions and help define how our safety infrastructure evolves as our products, users, and safety challenges grow.