Research Engineer - Data Infrastructure
Remote · Poland · Bulgaria · Full-time · Remote · Posted Oct 19, 2026
At a glance
- Employment
- Full-time
- Workplace
- Remote
- Location
- Remote · Poland · Bulgaria
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
- We are looking for a Research Engineer to join the research team at ElevenLabs, focused on the data infrastructure that powers our frontier AI models.
- You will own the systems that make world-class data possible by building large-scale data pipelines and designing data curation strategies.
Responsibilities
- Building large-scale data pipelines for collecting, processing, filtering, and transforming datasets used to train state-of-the-art models.
- Training models used in our data processing pipelines, such as classifiers, quality filters, and labeling models.
- Designing data curation strategies such as deduplication, quality scoring, labeling, and augmentation that measurably improve model performance.
- Creating tooling and infrastructure that lets researchers explore and train on massive datasets quickly and reliably.
Requirements
- Experience building data-intensive systems, ideally in support of machine learning training pipelines.
- Strong engineering skills in distributed data processing at scale (e.g., Kubernetes, or custom pipelines over large datasets).
- The capacity to autonomously evaluate how data quality, composition, and curation affect model outcomes, and to build the tooling to measure it.
Preferred qualifications
- Experience building or operating web crawlers.
Benefits
- Annual discretionary stipend for professional development
- Annual discretionary stipend to meet up with colleagues
- Annual company offsite in a new location
- Monthly co-working stipend if not located near one of the main hubs
Workplace
- Role is remote and can be executed globally.
Skills
- Kubernetes
