Senior Machine Learning Engineer

What you'll do

• Architect, design, and deploy LLM-powered systems for personalization and intelligent automation across Apple services.
• Lead research in large-scale representation learning, semantic modeling, and retrieval-augmented generation (RAG).
• Develop taxonomies, embeddings, and model architectures to analyze complex behaviors in high-dimensional, unstructured data.
• Drive LLM fine-tuning, evaluation, safety alignment, and optimization strategies for performant user experiences.
• Productize methods such as parameter-efficient adaptation, multi-agent orchestration, and RLHF.
• Build production-grade prototypes that enable reasoning over text, behavioral signals, and domain-specific knowledge at scale.
• Mentor researchers to improve experimentation, code quality, and scientific rigor.

What we're looking for

• Ph.D. in Computer Science, Machine Learning, NLP, Statistics, or a related field, or equivalent industry experience delivering production AI systems.
• At least 6 years of experience in an applied research or machine learning role.
• Expert knowledge of deep learning and modern NLP, including transformer architectures and foundation model adaptation.
• Experience with LLM model development, including fine-tuning, instruction tuning, and prompt engineering for domain-specific reasoning.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow, with experience deploying models in production systems.
• Strong understanding of distributed data processing systems (e.g., Spark) and large-scale experimentation.
• Proven ability to communicate research outcomes, architectural decisions, and technical tradeoffs to technical and non-technical stakeholders.
• Hands-on experience with RAG pipelines, vector-based search, inference optimization, and RLHF (preferred).