Senior Apps Applied Scientist

Apple Apple · Big Tech · Cupertino, CA +2 · Machine Learning and AI

This role focuses on designing, developing, and implementing sophisticated machine learning and AI models for creative applications, particularly image editing apps. It involves building end-to-end ML pipelines, prototyping AI features, developing AI tools, and deploying models into production. The role requires strong Python programming, experience with large-scale data, causal inference, LLM fine-tuning, RAG, and AI framework development.

What you'd actually do

  1. Designing, developing, and implementing sophisticated machine learning and AI models to solve complex problems, particularly for creative applications like our image editing apps.
  2. Building end-to-end ML pipelines, prototyping novel AI-powered features, developing AI tools, and collaborating closely with engineering, product, and marketing partners to bring intelligent solutions into production.
  3. Hands-on experience deploying AI/ML models into a production environment.
  4. Experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG).
  5. Experience developing or contributing to AI frameworks, APIs, or internal tools used by other teams.

Skills

Required

  • Python
  • Pandas
  • Scikit-learn
  • NumPy
  • statistical modeling
  • machine learning algorithms
  • supervised learning
  • unsupervised learning
  • classification
  • regression
  • clustering
  • large-scale data
  • distributed systems
  • Hadoop
  • Spark
  • causal inference
  • deploying AI/ML models
  • LLM fine-tuning
  • prompt engineering
  • retrieval-augmented generation (RAG)
  • rapid prototyping
  • reproduction
  • validation of research ideas
  • AI frameworks
  • APIs
  • internal tools

Nice to have

  • Strong product sense
  • passion for user experience
  • AI tools
  • frameworks
  • APIs
  • LLM-based applications

What the JD emphasized

  • PhD in Computer Science, Statistics, Mathematics, or a related quantitative field with 3+ years of relevant experience; or MS with 5+ years of experience in applied AI, machine learning, or statistical modeling.
  • 3+ years of programming proficiency with Python for data science and AI (e.g., Pandas, Scikit-learn, NumPy).
  • 3+ years of hands-on experience applying statistical modeling and machine learning algorithms for supervised and unsupervised learning (classification, regression, clustering, etc.).
  • 3+ years of experience working with large-scale data and distributed systems (e.g., Hadoop, Spark).
  • Working familiarity with causal inference models and techniques.
  • Hands-on experience deploying AI/ML models into a production environment.
  • Experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG).
  • Experience with rapid prototyping, reproduction, and validation of research ideas.
  • Experience developing or contributing to AI frameworks, APIs, or internal tools used by other teams.

Other signals

  • driving innovation in building scalable ML and AI solutions
  • enhance our product intelligence
  • improve automation
  • expand our AI-driven capabilities
  • designing, developing, and implementing sophisticated machine learning and AI models
  • building end-to-end ML pipelines
  • prototyping novel AI-powered features
  • developing AI tools
  • bringing intelligent solutions into production
  • deploying AI/ML models into a production environment
  • LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG)
  • rapid prototyping, reproduction, and validation of research ideas
  • developing or contributing to AI frameworks, APIs, or internal tools