Senior Machine Learning Manager, Answers, Search & Knowledge Platforms

Apple Apple · Big Tech · Santa Clara, CA +3 · Machine Learning and AI

This role manages a team focused on enhancing Siri and Apple products by advancing real-time augmented information retrieval and generation, knowledge graph engineering, and LLM-powered answer generation for user knowledge questions. It involves E2E knowledge graph construction, serving, and understanding user intent to deliver knowledge-driven user experiences.

What you'd actually do

  1. drive E2E Apple Knowledge Graph engineering to generate answers and experiences for users' knowledge questions.
  2. lead the team in developing advanced NLP and ML models to understand user query entities and intent, retrieve the relevant entities and facts from the knowledge graph, and generate high-quality answers and dialog/experiences using LLM-powered models.
  3. devising the product vision and strategy, evangelizing it, executing the plan, and delivering a high-quality end-user experience.
  4. work with a wide range of organizational partners across design, product and marketing, software engineering, data science, foundation models, and machine learning and profoundly impact billions of Apple users worldwide.

Skills

Required

  • Search
  • natural language processing/understanding
  • conversational AI
  • Machine Learning
  • Ranking
  • Relevance and Metrics
  • E2E knowledge graph technologies

Nice to have

  • Product Vision
  • Ability to manage long-term strategy and short-term deliverables.
  • Strong engineering leadership and fundamentals.

What the JD emphasized

  • 8+ years of experience leading engineering/applied research/ML experiences in search, natural language processing/understanding, and conversational AI.
  • MS or Ph.D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field
  • Strong background and experience in Search and related technologies (Machine Learning, Ranking, Relevance and Metrics)
  • Strong engineering and R&D experience in E2E knowledge graph technologies

Other signals

  • LLM-powered models
  • realtime augmented information retrieval and generation
  • NLP and ML models
  • knowledge graph construction
  • serving