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 an ML & search engineer you will help us build and apply ML solutions to scale new features utterance understanding and natural language generation faster across different languages - with a special focus on Search and Question Answering systems across Apple products. You will 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 - Scale search and search-based systems across languages- Build and automate evaluation of LLM based information retrieval- Develop mechanisms to automate data creation and data filtering across different languages - Find innovative solutions to scale fine-tuning approaches to multiple languages - Build and ship ML based products at high quality for worldwide Apple customersWere looking for a self-starting upbeat individual with excellent written and communication skills hardworking person who is a great teammate but not afraid to question assumptions and take initiative. If you feel this is you wed love to hear from you.
Expertise in search systems and related technologies including indexing retrieval and ranking.
Proficiency on software engineering best practices design and comfortable working in modern cloud container based stacks.
Experience shipping production grade ML or DL based applications including proficiency on Python and modern ML frameworks such as TensorFlow PyTorch or JAX.
Experience with multilingual data machine translation and understanding of the complexities and tradeoffs involved when scaling to non-English languages.
MS or PhD in Computer Science Artificial Intelligence Machine Learning or related field
Excellent interpersonal skills; able to work in a team as well as independently; can take and give feedback; can iterate on a solution in a collaborative environment.
Experience with or strong interest in agents tool-use planning and multi-step reasoning
Experience with RAG LLM Reasoning and LLM Agent and/or Machine Translation.
Optionally experience with LLM reinforcement learning techniques.
Optionally experience with building on-device software and models.
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