Senior NLP ML Engineer for Personal Intelligence

Apple, Inc.; Cupertino (CA); Presencial; USD 185.000 - 325.000; Jornada completa

Descripción de la vacante

Apple, Inc. in Cupertino, CA is seeking a Senior Machine Learning Engineer focusing on NLP for Personal Intelligence & Experiences (PIEx).

You will build and optimize multimodal input pipelines and translate cutting-edge NLP research into production features across Apple platforms. You will design experiments, implement scalable ML pipelines, and collaborate with language experts to meet language-specific requirements while advancing user-facing experiences.

Formación

• 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-quality Python modules.
• Solid background in machine learning, data science, natural language processing, or statistics.

Responsabilidades

• Researching techniques to enhance model behavior.
• Development and maintenance of scalable modeling pipelines that support multiple languages and production deployment.
• Defining robust automated evaluation metrics to facilitate model quality improvement through hillclimbing.
• Conducting failure analysis to identify and address the shortcomings of our models.
• Curation and synthesis of representative training and evaluation data.
• Implementation of experiments and simulations to assess the value of model modifications.
• Collaboration with language experts and QA to refine modeling approach in consideration of language-specific requirements

Conocimientos

Python

NLP

Swift

Educación

MS or PhD in Computer Science or related field

Descripción del empleo

Apple, Inc. in Cupertino, CA is seeking a Senior Machine Learning Engineer focusing on NLP for Personal Intelligence & Experiences (PIEx).

You will build and optimize multimodal input pipelines and translate cutting-edge NLP research into production features across Apple platforms. You will design experiments, implement scalable ML pipelines, and collaborate with language experts to meet language-specific requirements while advancing user-facing experiences.