AI Researcher – Multilingual Data

📋 Description

• Design and conduct research focused on multilingual datasets, including data collection, filtering, deduplication, quality assessment, and optimization.
• Develop innovative strategies for low-resource and long-tail languages through advanced sampling, data augmentation, and curriculum learning techniques.
• Research and improve multilingual large language models by enhancing cross-lingual transfer, alignment, robustness, and representation learning.
• Build, maintain, and refine multilingual evaluation benchmarks to measure model quality and performance across languages.
• Collaborate closely with machine learning engineers and researchers to influence training pipelines, model architectures, and production deployment strategies.
• Publish research findings at leading AI and NLP conferences while contributing to open-source initiatives when appropriate.

🎯 Requirements

• Advanced background in Natural Language Processing, Machine Learning, Artificial Intelligence, or a closely related field.
• Proven research experience in multilingual or cross-lingual language modeling with publications at recognized conferences or journals such as ACL, EMNLP, NeurIPS, ICML, or ICLR.
• Hands-on experience working with large-scale multilingual text datasets and modern machine learning workflows.
• Strong understanding of multilingual tokenization, vocabulary design, transfer learning, multilingual representation learning, dataset quality assessment, filtering techniques, and bias mitigation.
• Proficiency in Python and modern deep learning frameworks such as PyTorch or JAX.
• Ability to work independently, manage research initiatives, and deliver high-quality results in a fast-moving startup environment.
• Experience with low-resource languages, non-Latin scripts, multilingual evaluation benchmarks (XTREME, FLORES, TyDi QA), open-source NLP projects, or large language model training is considered a strong advantage.

🎁 Benefits

• Competitive compensation package.
• Meaningful equity opportunity within an early-stage, high-growth company.
• Significant ownership over research direction and technical decision-making.
• Opportunity to balance academic research with real-world production impact.
• Access to large-scale multilingual datasets, modern AI infrastructure, and rapid experimentation cycles.
• Collaborative environment that values innovation, research excellence, and continuous learning.