Staff Research Engineer, Multilingual AI Data Pipelines

reflectionai; San Francisco, New York (CA, NY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health insurance

Meals provided in office

Parental leave (22 weeks)

Unlimited vacation (US)

Job summary

Reflection is a research lab focused on making intelligence open and accessible. We design and operate large-scale multilingual data pipelines to support multilingual language models, with emphasis on data quality, cultural fidelity, and safety across languages.

You will lead small research projects and collaborate with cross-functional teams to push the boundaries of multilingual AI, including data preprocessing, evaluation, and experiments to improve efficiency and coverage across high- and

Qualifications

• Strong software engineering fundamentals and comfort processing web-scale datasets in distributed environments.
• Experience building large-scale data pipelines for language models, machine translation, speech, or search — ideally covering more than one language.
• Fluency or working proficiency in at least one language other than English, and genuine curiosity about how languages differ.
• A rigorous, measurement-first mindset: you prove a data change helped rather than assuming it did.
• Navigate trade-offs between research objectives and practical engineering realities.
• Comfortable with ambiguity and high ownership in a small, fast-moving team.

Responsibilities

• Design and operate large-scale multilingual data pipelines — sourcing, cleaning, deduplication, language identification, and script normalization across high- and low resource languages.
• Define and enforce quality bars for multilingual corpora, including translation quality, cultural fidelity, toxicity, and contamination checks.
• Design and run scientific experiments to advance our understanding of scaling large language models to improve multilingual data efficiency.
• Lead small research projects independently while collaborating on larger initiatives.
• Build evaluation sets and diagnostics that expose where model behavior degrades by language, register, or domain, and close those gaps with targeted data.
• Work with pre-training, mid-training, and post-training teams to land measurable, step-function improvements in multilingual capability.

Skills

Software engineering

Distributed data processing

Multilingual NLP experience

Language model data pipelines

Job description

Reflection is a research lab focused on making intelligence open and accessible. We design and operate large-scale multilingual data pipelines to support multilingual language models, with emphasis on data quality, cultural fidelity, and safety across languages.

You will lead small research projects and collaborate with cross-functional teams to push the boundaries of multilingual AI, including data preprocessing, evaluation, and experiments to improve efficiency and coverage across high- and