AI Researcher - Multilingual Data（远程职位）

这条招聘信息来自 Featherless AI，岗位是 AI Researcher - Multilingual Data。职位属于「IT 与编程」类别，完全远程。公司不限制候选人的居住地，在任何地方都可以申请。

招聘信息里列出的主要工具是：Python、Machine Learning。简历上最好能给出正是这几项能力的具体例子。

公司没有公布具体数字，这一项会在面试时谈定。对工作时间，招聘信息没有提出任何条件。

这个职位通过了自动核查：凡是要求外国工作许可、签证担保、特定国籍，或者必须居住在指定国家的招聘信息，都不会进入列表。

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

Originally posted on Himalayas