AI Researcher – Multilingual Data
At a glance
Mid-level AI Research role at Featherless AI. Remote · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Design multilingual data studies, covering collection, filtering, duplicate removal and quality checks
- Create sampling, augmentation and curriculum approaches for low-resource and long-tail languages
- Improve cross-language transfer, alignment and robustness in large language models
- Build benchmarks for measuring multilingual model performance and work with teams on training pipelines
- Publish findings and turn research into production model improvements
What you bring
- A strong NLP or machine learning research background focused on multilingual or cross-lingual modeling
- Research publications at respected conferences or journals, such as ACL, EMNLP or another listed venue
- Experience handling large text collections in multiple languages
- Knowledge of multilingual tokenization, dataset quality and bias, and transfer learning
- Ability to prototype in Python using a modern ML framework such as PyTorch or another listed framework
Who this fits
This mid-level remote role suits a researcher who can work independently and move research into practical model changes. You’ll balance research publication with implementation alongside engineering and research teammates.
From the employer
About the Role
We’re looking for an AI Researcher focused on multilingual data to help us build and scale next-generation language models across diverse languages and domains. You’ll own research and execution around data sourcing, curation, evaluation, and training strategies for multilingual and low-resource languages, with a strong emphasis on publishing high-quality research and translating it into production systems.
This role is ideal for someone who enjoys working close to the frontier: balancing papers, prototypes, and real-world impact in a fast-moving startup environment.
What You’ll Do
Design and execute research on multilingual datasets, including data collection, filtering, deduplication, and quality measurement
Develop strategies for low-resource and long-tail languages (sampling, augmentation, curriculum design)
Research and improve cross-lingual transfer, alignment, and robustness in large language models
Build and maintain evaluation benchmarks for multilingual performance
Collaborate with engineers and researchers on training pipelines and model architecture decisions
Publish research at top venues (e.g., ACL, EMNLP, NeurIPS, ICML, ICLR) and contribute to open-source when appropriate
Translate research insights into practical improvements in production models
What We’re Looking For
Strong background in NLP / ML research, with a focus on multilingual or cross-lingual modeling
Publication record at respected conferences or journals (ACL, EMNLP, NeurIPS, ICML, ICLR, etc.)
Experience working with large-scale text datasets across multiple languages
Solid understanding of:
Tokenization and vocabulary design for multilingual models
Data quality metrics, filtering, and dataset bias
Transfer learning and multilingual representation learning
Comfortable prototyping in Python with modern ML frameworks (PyTorch, JAX, etc.)
Ability to operate independently and ship research in a startup pace environment
Nice to Have
Experience with low-resource languages or non-Latin scripts
Open-source contributions in NLP or data tooling
Experience training or evaluating large language models
Familiarity with multilingual benchmarks (e.g., XTREME, FLORES, TyDi QA)
Why Join Us
Real ownership over research direction and impact
A team that values papers and production
Access to meaningful scale: large datasets, modern infrastructure, and fast iteration
Competitive compensation and meaningful equity at an early stage