Applied ML engineer in software localization

The Software Localisation team powers the tooling, features and processes used to create an exceptional localised experience for Apple’s international customers. We are responsible for localisation workflows, framework-level localisation support, localised OS features, and internal localisation tools used to create high quality experience across all of Apple’s software products around the world. We are looking for a creative, motivated, and passionate engineer who will work cross-functionally and globally to deliver the next generation of ML tooling and Apple Intelligence features for international locales.

• Leading the exploration and application of Large Language Models (LLMs) for performing data synthesis and translation tasks
• Translating the latest research into high-quality systems and models that can be practically applied to further improve model localisation
• Actively engaging in all aspects of model development, from ideation, training, experimentation, evaluation to deployment.
• Collaborating with translation, localisation quality, project management and engineering teams to develop and implement solutions
• Developing and maintaining features and tools to help facilitate the data and model localisation process

• Experience with Machine Learning (ML), with a particular emphasis on Large Language Models (LLMs), Natural Language Processing (NLP) and building agentic workflows.
• Strong programming skills in Python, Swift, C or C++ or other language
• Будет плюсом: BS, MS or PhD in Computer Science, Computational Linguistics, Artificial Intelligence, or Machine Learning; Proven ability to comprehend, interpret, and apply cutting-edge research into consumer-oriented products; Comprehensive knowledge and hands-on experience with fine-tuning approaches, prompt optimization and training models; Experience adapting pre-trained LLMs for downstream tasks; Proficiency using open-source ML toolkits and frameworks; Experience in software localisation / internationalisation; Fluency in English and native-level proficiency in an additional language (reading, writing, and speaking)

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