Aiml - Sr Machine Learning Engineer, Data and ML Innovation

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

Machine Learning Engineer at Apple focused on innovating and applying state-of-the-art ML research to complex data problems, specifically for Apple Intelligence. The role involves designing and developing a data generation and curation framework for foundation models, building evaluation pipelines, and exploring new methods for synthetic data creation across vision, text, and audio. The position also emphasizes collaboration with multidisciplinary teams and potentially publishing research.

What you'd actually do

  1. Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data.
  2. Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets.
  3. Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models.
  4. Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data.
  5. Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments.

Skills

Required

  • Python
  • PyTorch
  • Jax
  • computer vision
  • natural language processing
  • machine learning
  • data-centric machine learning
  • multi-modal foundation models
  • generative AI
  • multi-modal LLM

Nice to have

  • 3+ years of experience with developing and evaluating ML applications
  • understanding and improving data quality
  • multimodal large language model or image/video generation model training
  • Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas

What the JD emphasized

  • critical role of innovating and applying state of the art research in ML
  • design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models
  • build robust model evaluation pipelines
  • publishing and presenting at premier academic venues
  • Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
  • Deep understanding in multi-modal foundation models.
  • Staying on top of emerging trends in generative AI and multi-modal LLM.
  • Strong publication record in relevant conferences

Other signals

  • develop new insightful practices that will change how we understand data
  • design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models
  • build robust model evaluation pipelines