At a glance
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- London
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.
About the role
- You will take ownership of the datasets and evaluation workflows that underpin our AI Safety work.
- You'll turn real-world product data into reliable, well-structured datasets for training and evaluating models, and help build the processes and infrastructure to continuously assess how those models perform in production.
- This is a hands-on role at the intersection of data science, ML, AI safety, and policy.
Responsibilities
- Own safety datasets end-to-end: collection, cleaning, labelling, quality control, versioning, and readiness for training and evaluation.
- Translate safety policy into clear, consistent labelling and evaluation criteria, working closely with policy specialists.
- Design and manage labelling processes, including sourcing, onboarding, and overseeing external contributors to a high quality bar.
- Build evaluation workflows for models in production, using real-world data to track performance and surface issues.
- Develop lightweight Python/SQL pipelines and tooling to make data work faster and reproducible, partnering with ML engineers on what "training-ready" looks like.
Requirements
- Experience as a Data Scientist, or similar, working with real-world datasets and ML models.
- Strong grasp of what makes a good dataset: collection, cleaning, sampling, labelling, quality control, evaluation.
- Comfortable with Python and SQL for analysis and practical data workflows.
- Strong critical thinking and judgement - comfortable with ambiguity and nuance, and able to turn complex guidelines into consistent, scalable decisions.
- Autonomous and a clear communicator, able to work across disciplines (policy, engineering, research) in a fast-moving, still-forming environment.
Preferred qualifications
- Experience in AI safety, trust & safety, content moderation, or fraud/abuse detection.
- Experience building datasets or evaluation frameworks, or with adversarial/safety-focused ML.
- Experience managing human-in-the-loop labelling processes, dataset versioning, or ML pipeline tooling.
- Experience operationalising guidelines with policy or legal teams.
Benefits
- Annual discretionary professional development stipend
- Annual discretionary social travel stipend
- Annual company offsite
- Monthly co-working stipend
Workplace
- This role is based in London, where you'll work closely with our AI Safety and Policy teams.
Skills
- Python
- SQL
