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Senior Machine Learning Engineer

Apple· Apple Services Engineering (ASE)
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Cupertino, CA, Seattle, WA$184.7k - $324.8kfull-timePosted 1mo ago

About the role

Senior ML Engineer focusing on Generative AI, LLM architectures, and advanced NLP to build foundational intelligence capabilities across Apple Services, from research to production deployment, with leadership responsibilities and cross-functional collaboration.

Responsibilities

  • Architect, design, and deploy LLM-powered systems that unlock new capabilities for personalization, intelligent automation, and customer understanding across Apple’s services ecosystem.
  • Lead research in areas such as large-scale representation learning, semantic modeling, topic induction, natural language understanding, and retrieval-augmented generation (RAG).
  • Develop and evolve taxonomies, embeddings, and model architectures capable of disentangling complex user or content behaviors in high-dimensional, unstructured data.
  • Drive LLM fine-tuning, evaluation, safety alignment, and optimization strategies to ensure performant, compliant, and frictionless user experiences.
  • Explore and productize methods such as parameter-efficient adaptation, multi-agent orchestration, active learning, RLHF, and novel inference optimization techniques.
  • Collaborate with engineering, product, and design organizations to translate ambiguous problem spaces into robust ML systems with measurable business and customer impact.
  • Build prototypes and production-grade solutions that advance Apple’s ability to reason over text, behavioral signals, and domain-specific knowledge at scale.
  • Contribute to Apple’s leadership in AI through patent filings, publications, and internal thought leadership.
  • Mentor and elevate other researchers, fostering excellence in experimentation, code quality, communication, and scientific rigor.

Qualifications

  • 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 retrieval-augmented generation (RAG) pipelines and vector-based semantic search systems.
  • Representation learning and semantic embeddings for clustering, categorization, and content understanding.
  • Model evaluation frameworks for language quality, relevance, hallucination, and safety.
  • Inference optimization techniques (quantization, distillation, model compression).
  • Understanding of reinforcement learning, policy alignment, or RLHF for improving interactive AI systems.
  • Experience developing personalization, ranking, or optimization algorithms at scale.
  • Proven experience in the architectural design and develop RL or multi-armed bandit experiment platform.
  • A record of publications in top-tier ML/AI venues or patent filings demonstrating novel research contributions.

Skills

Required:LLM development and fine-tuningPythonPyTorch or TensorFlowRAG and vector databasesDistributed systems (e.g., Spark)NLP and transformer architecturesCommunication with stakeholders
Nice to have:Reinforcement learning / RLHF

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • range of discounted products and free services
  • reimbursement for certain educational expenses including tuition
  • discretionary bonuses or commission payments (where eligible)
  • relocation assistance (where eligible)
  • Apple shareholder opportunities through discretionary employee stock programs
  • Employee Stock Purchase Plan
Last updated Sep 18, 2026. Interested? Apply on the company site.

About Apple

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