49 jobs for "ML Engineer, Apple Foundation Models"

Language Engineer (Danish), Global Siri

At Apple

Posted on Oct 15

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Language Engineer (Arabic), Global Siri

At Apple

Posted on Oct 15

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Applied AI & Data Engineer - Business & Education

At Apple - Cupertino

Posted on Oct 14

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Machine Learning Engineer, SIML

At Apple - Cupertino

Posted on Oct 12

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Staff Machine Learning Engineer, Analytics & Data Engineering

At Apple - Cupertino

Posted on Oct 16

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Machine Learning Engineer, Foundation Model Services

At Apple - Santa Clara

Posted on Oct 16

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Machine Learning Engineer, Foundation Model Services

At Apple - Santa Clara

Posted on Oct 16

View job Apply on company site

Applied AI & Data Engineer - Business & Education

At Apple - Cupertino

Posted on Oct 14

View job Apply on company site

Machine Learning Engineer, SIML

At Apple - Cupertino

Posted on Oct 12

View job Apply on company site

Apple

Language Engineer (Danish), Global Siri

Posted 24 days ago

Apply on company site View full job

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Play a part in the next revolution of machine learning technology! Siri assists hundreds of millions of people, in dozens of languages, every day, and Global Siri is the team that teaches Siri each one of them.

We own the product end-to-end, from Speech Recognition and Natural Language Understanding through to Response. We are looking for an engineer with deep expertise in either Machine Learning or Software Engineering, and practical working knowledge of the other, to shape the future of Siri for Danish users.

Your work will range across multiple disciplines, including employing advanced Large Language Models (LLMs), adopting models for global markets, running data experiments, and engineering scalable software to deliver highly personalized, culturally relevant experiences for our customers.

Description
As a member of our dynamic and fast-paced group, you will play a key role in crafting innovative, end-to-end solutions that delight millions of customers across the globe. You will act as the technical anchor for the Danish market, leading work streams to design and implement large-scale ML and GenAI solutions that advance our customer experience.

This position sits squarely at the intersection of Machine Learning, Data, and Software Engineering. Whether you are a strong Software Engineer who has applied ML to production systems, or an ML expert with solid coding skills, you will leverage large language models (LLMs), agentic approaches to tasks, and data generation methods to build real-world systems.

You will work with partner teams across Apple, sharing your expertise and bringing architectural proposals that account for international market nuances, so that Siri feels genuinely native to Danish users.

Join us as we build the foundation of Siri AI for users around the world!

Preferred Qualifications
Hands-on experience with large language models: fine-tuning, prompt and context engineering, evaluation, and inference optimization, including agentic systems, tool calling, or retrieval-augmented generation.
Experience with speech technologies such as ASR, TTS, or pronunciation modeling.
Experience adapting models or products across languages and markets - multilingual and cross-lingual modeling, transfer learning, or low-resource settings.
Ability to formulate a research problem, design, experiment, implement and communicate solutions.
Product focus with a strong emphasis on end-user experience.
Experience writing software in Python, Swift, Objective-C, C++ or C; experience on Apple platforms preferred.
M.S, Ph.D. in Computer Science or a related field, or equivalent practical experience.

Minimum Qualifications
Professional-level fluency in Danish, with deep familiarity with the culture and idiom of Denmark.
Experience in applying machine learning and NLP techniques to deliver products, with a solid understanding of ML concepts
Strong skills in software design and programming across different paradigms, including testing and maintainability, with experience contributing to large production code bases.
Experience working with data at scale, including building or curating datasets, analyzing results, and making data-driven decisions.

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Industry: Technology: Manufacturing

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