Machine Learning Engineer

Responsibilities

• 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

Requirements

• 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
• Ability to collaborate with researchers and translate research needs into production systems

Preferred Qualifications

• 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
• Experience with data quality evaluation at scale

About the Company

We are a high-caliber team building models used globally, focusing on linguistic diversity and model generalization beyond English-speaking markets.