Senior Machine Learning Engineer, Analytics & Data Engineering

Apple Apple · Big Tech · Seattle, WA +2 · Machine Learning and AI

Senior Machine Learning Engineer focused on building and innovating AI/ML foundations for Apple's services, ensuring security, privacy, and scalability. The role involves researching and developing state-of-the-art AI/ML solutions, designing secure and performant systems, and collaborating with broader teams. Requires strong engineering foundations, experience with distributed systems, and modern AI/ML frameworks.

What you'd actually do

  1. Research and develop state-of-the-art AI/ML solutions and tools that transform how we train, deploy, and monitor models that power features in Apple Products.
  2. You will design secure, private, and highly performant systems, ensuring our systems respect and protect user privacy as a core engineering feature.
  3. Act as a technical leader. You will collaborate with broader teams across Apple, actively participating in design discussions, giving and receiving constructive feedback, and mentoring junior engineers.
  4. Participate in our highly collaborative environment to elevate our engineering standards. From design reviews and rigorous code reviews to robust test automation, you will ensure our AI/ML systems are maintainable and resilient.

Skills

Required

  • Python
  • Java/Scala
  • data structures
  • algorithms
  • system design
  • traditional machine learning algorithms
  • cutting edge genAI technologies
  • PyTorch
  • TensorFlow
  • JAX
  • large-scale distributed data processing technologies
  • Ray
  • Spark

Nice to have

  • ML infrastructure (services, pipelines, frameworks, deployment tooling)
  • Kubernetes
  • MLflow
  • Generative AI and LLM assistants
  • Claude
  • Gemini
  • communication skills
  • autonomy

What the JD emphasized

  • state-of-the-art AI/ML solutions
  • secure, private, and highly performant systems
  • core engineering feature
  • technical leader
  • mentoring junior engineers
  • highly collaborative environment
  • rigorous code reviews
  • robust test automation
  • maintainable and resilient

Other signals

  • AI/ML foundation
  • AI/ML solutions
  • AI/ML systems
  • large-scale distributed data processing
  • modern AI/ML frameworks