NLP ML Research Engineer - Multilingual Production Pipelines

NLP PEOPLE; United States; Remote; USD 159,000 - 264,000; Full time

Benefits offered by this job

Employee stock options

Discretionary RSU awards

Discounted products

Job summary

Reputed company in Cupertino, California is seeking a Machine Learning Research Engineer to advance multilingual NLP capabilities across its language input platforms. You will design and refine training and evaluation pipelines for production-ready models.

You will collaborate with cross-functional teams on data curation, experimentation, and system integration, with focus on global languages and scalable NLP features. Strong Python and ML background required.

Qualifications

• MS or PhD in Computer Science or related field with at least 2 years of industry experience.
• Strong Python programming skills, with experience developing production-grade Python modules.
• Solid background in machine learning, data science, natural language processing, or statistics.

Responsibilities

• Develop and maintain modeling pipelines for multi-language production deployment.
• Define robust automated evaluation metrics to guide model improvement.
• Perform failure analysis to understand model shortcomings.
• Research techniques to improve model behavior.
• Curate and synthesize training/evaluation data.
• Implement experiments to assess value of model changes.
• Collaborate with language experts and QA on language-specific requirements.

Skills

Python

ML/NLP

Statistics

Industry experience

Education

MS/PhD in CS or related

Job description

Reputed company in Cupertino, California is seeking a Machine Learning Research Engineer to advance multilingual NLP capabilities across its language input platforms. You will design and refine training and evaluation pipelines for production-ready models.

You will collaborate with cross-functional teams on data curation, experimentation, and system integration, with focus on global languages and scalable NLP features. Strong Python and ML background required.