Machine Learning Engineer — Multilingual Data

Design, build, and maintain large-scale multilingual datasets across high- and low-resource languages

Develop data pipelines for collection, cleaning, normalization, deduplication, and labeling

Implement quality filters using statistical, heuristic, and model-based methods

Work with researchers to define language coverage, benchmarks, and evaluation metrics

Analyze dataset bias, coverage gaps, and failure modes across regions and scripts

Support training, fine-tuning, and distillation workflows with high-quality multilingual data

Continuously iterate on datasets based on model performance and real-world usage

3+ years of experience as an ML Engineer, Applied Scientist, or similar role

Strong experience working with multilingual or non-English datasets

Solid understanding of NLP fundamentals (tokenization, embeddings, language modeling)

Experience building scalable data pipelines (Python, Spark, Ray, or similar)

Familiarity with Unicode, scripts, tokenization challenges, and language-specific quirks

Comfort collaborating with researchers and translating research needs into production systems

Experience with low-resource languages or multilingual benchmarks (e.g. FLORES, XTREME)

Exposure to LLM training, fine-tuning, or distillation

Linguistics background or experience working with native language experts

Contributions to open-source datasets or ML tooling