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Apple Machine Learning Engineer SII Spain, Catalonia, Barcelona 451872717
21.04.2025
In Global Siri, we are responsible for the end-to-end user experience in all Siri markets. This means we build new features and scale them across Siri languages and devices. As a Senior ML engineer in Global Siri, you will help us build and apply ML solutions to scale new features, utterance understanding and natural language generation faster across different languages. You should be able to work with large scale systems, write high quality code and are comfortable in contributing to existing systems and developing new ones. Communication skills will be required to coordinate work across multiple teams. Specific responsibilities include: - Work on cutting-edge technology at the intersection of agents & multilinguality - Understand how agentic LLMs learn capabilities across languages- Develop mechanisms to automate data creation and data filtering across different languages - Find innovative solutions to scale fine-tuning approaches to multiple languages - Devise automated approaches to evaluate the performance of agents across multiple languages
- Expertise in innovative LLMs and in-depth knowledge of the latest advancements in the field and a deep understanding of LLM fine-tuning.
- Experience with multilingual data, machine translation and understanding of the complexities and tradeoffs involved when scaling to non-English languages.
- Proficiency in Python and modern ML frameworks such as TensorFlow, PyTorch or JAX.
- Excellent interpersonal skills; happy to work in a team as well as independently; can take and give feedback; can iterate on a solution in a collaborative environment.
- MS or PhD in Computer Science , Artificial Intelligence, Machine Learning or equivalent
- Experience with RAG, LLM Reasoning, and LLM Agent and/or Machine Translation.
- Experience shipping production grade ML or DL based applications.
- Experience with or strong curiosity about agents, tool-use, planning and multi-step reasoning
- Optionally experience with LLM reinforcement learning techniques.
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