Spanish Siri ML Engineer — Multilingual NLP & GenAI

Apple Inc.

Bellprat

Presencial

EUR 90.000 - 120.000

Jornada completa

14 días+
Generador de candidaturas

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Ventajas ofrecidas por este puesto de trabajo

Health insurance

Descripción de la vacante

Apple Inc. in Barcelona seeks an engineer with deep expertise in machine learning or software engineering to shape the future of Siri for Spanish users.

You will work across ML, NLP, and scalable software, leveraging LLMs, data experiments, and agentic approaches to create native, high-quality experiences. You will collaborate with cross-functional teams at Apple to design and implement end-to-end systems, ensuring production-grade reliability and culturally relevant features for millions of

Formación

  • Professional-level fluency in Spanish with deep cultural understanding.
  • Experience applying machine learning and NLP to deliver products; solid ML concepts.
  • Strong software design, testing, and maintainability; experience with large production codebases.
  • Experience working with data at scale: building/curating datasets, analyzing results, data-driven decisions.

Responsabilidades

  • Lead end-to-end ML/GenAI solutions for Spanish Siri and global users.
  • Architect and implement scalable ML/software systems across Apple platforms.
  • Collaborate with cross-functional teams to account for market nuances and deliver native user experiences.

Conocimientos

Spanish fluency
ML concepts
Software design
Data at scale

Educación

MS/PhD in CS or related field

Herramientas

Python
Swift
Objective-C
C++
C

Descripción del empleo

Apple Inc. in Barcelona seeks an engineer with deep expertise in machine learning or software engineering to shape the future of Siri for Spanish users.

You will work across ML, NLP, and scalable software, leveraging LLMs, data experiments, and agentic approaches to create native, high-quality experiences. You will collaborate with cross-functional teams at Apple to design and implement end-to-end systems, ensuring production-grade reliability and culturally relevant features for millions of

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