Senior Machine Learning Engineer

What you'll do

• Architect and deploy LLM-powered systems for personalization, automation, and customer understanding 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 data.
• Execute LLM fine-tuning, evaluation, safety alignment, and optimization strategies for production environments.
• Productize advanced techniques including multi-agent orchestration, RLHF, and inference optimization.
• Build prototypes and production-grade solutions that enable reasoning over text and behavioral signals at scale.
• Contribute to company leadership through patent filings, publications, and internal technical thought leadership.
• Mentor other researchers in 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 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 both technical and non-technical stakeholders.
• Experience with RAG pipelines, inference optimization, RLHF, or publication in top-tier venues (preferred).