Senior Machine Learning Engineer (generative Ai)

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

Senior Machine Learning Engineer focused on Generative AI, responsible for converting high-level goals into concrete requirements, implementing, evaluating, and shipping AI/ML technologies for data quality or user-facing features. Requires experience in building large-scale ML systems, generative AI models, and working with large datasets, with a strong emphasis on shipping production-ready solutions.

What you'd actually do

  1. converting abstract, high-level goals into concrete, measurable requirements
  2. proposing, implementing, evaluating, and shipping different AI/ML technologies to improve data quality or deliver user facing features
  3. collaborating with various partners, including engineering orgs and designers to architect the best overall system
  4. develop innovative AI/ML solutions that enhance user experiences
  5. hands-on in building robust, real-world solutions

Skills

Required

  • building large-scale machine learning systems
  • generative AI models (e.g. Transformers, LLMs, VLMs, MLLMs)
  • computer vision
  • knowledge graph
  • large-scale and real-world datasets
  • PyTorch
  • TensorFlow
  • Scikit-learn
  • Spark
  • cloud platforms (AWS, GCP, or Azure)

Nice to have

  • Masters or PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields
  • shipping a complex AI system, including research and leveraging generative AI models

What the JD emphasized

  • 5+ years of experience in building large-scale machine learning systems
  • 2+ years of experience in one or more of the following ML areas: generative AI models (e.g. Transformers, LLMs, VLMs, MLLMs), computer vision or knowledge graph
  • Experience shipping a complex AI system, including research and leveraging generative AI models

Other signals

  • shipping AI/ML technologies
  • user facing features
  • building robust, real-world solutions
  • shipping a complex AI system