Machine Learning Engineer, International Data Engineering

Apple Apple · Big Tech · Cupertino, CA · Software and Services

Machine Learning Engineer focused on localizing and scaling LLMs and NLP models for Apple's international customers. The role involves end-to-end model development, including training, experimentation, evaluation, and deployment, with a focus on data-driven quality programs and building tools for software translation.

What you'd actually do

  1. Actively engaging in all aspects of model development, from ideation, training, experimentation, evaluation to deployment
  2. Helping define a scalable, data driven quality program to continuously improve ML based products and features globally
  3. Collaborating with translation, Localization quality, project management and engineering teams to develop and scale the approach with a focus on the end user and the product quality
  4. Developing and maintaining features, frameworks and tools to help facilitate the software translation process

Skills

Required

  • Machine Learning (ML)
  • Large Language Models (LLMs)
  • Natural Language Processing (NLP)
  • end to end machine learning systems development
  • training models
  • fine-tuning approaches
  • Python

Nice to have

  • handling large datasets
  • data analytics pipelines for natural language based products
  • cutting-edge research into consumer-oriented products
  • PyTorch
  • TensorFlow
  • OpenNMT
  • software Localization / internationalization
  • Native-level foreign language skills
  • languages and culture
  • Published research in the field of Machine Learning or AI

What the JD emphasized

  • robust understanding of large language models (LLMs), generative AI, Natural Language Processing (NLP) and Machine Translation (MT)
  • Strong engineering fundamentals and a passion for this area are required
  • Experience with Machine Learning (ML), with a particular emphasis on Large Language Models (LLMs) and Natural Language Processing (NLP)
  • Hands-on experience developing end to end machine learning systems: defining and creating metrics and datasets, training models and performing error triaging
  • Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models

Other signals

  • design, implement and qualify Apple Intelligence features globally
  • architect the future of localizing and scaling Machine Learning models and datasets
  • Actively engaging in all aspects of model development, from ideation, training, experimentation, evaluation to deployment
  • Developing and maintaining features, frameworks and tools to help facilitate the software translation process