Sr. Machine Learning Engineer, Siri Speech

Cupertino, CA, US • Posted 4 hours ago • Updated 4 hours ago
Full Time
On-site
Fitment

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Job Details

Skills

  • Natural Language
  • Deep Learning
  • Privacy
  • Artificial Intelligence
  • MSC
  • Statistics
  • Python
  • PyTorch
  • TensorFlow
  • JAX
  • Data Processing
  • Management
  • Unsupervised Learning
  • Evaluation
  • Cloud Computing
  • Amazon Web Services
  • Google Cloud
  • Google Cloud Platform
  • Microsoft Azure
  • Docker
  • Kubernetes
  • Software Engineering
  • Testing
  • Code Review
  • Version Control
  • Machine Learning (ML)
  • Computer Science
  • Training
  • Machine Learning Operations (ML Ops)
  • Natural Language Processing
  • Real-time

Summary

We are a group of engineers/researchers responsible for advancing Siri Conversational AI at Apple. Our mission is to build cutting-edge infrastructure, datasets, and models that empower Siri with capabilities across natural language understanding, dialog generation, speech synthesis and recognition, and multi-modal interaction. We apply these technologies to create engaging, intelligent, and personalized conversational experiences for millions of Apple users!\\n

We believe that the most impactful breakthroughs in deep learning emerge when we address real-world problems at scale while we preserve user privacy. Siri presents a unique and rich set of challenges-from robust understanding of diverse user intents to fluid, contextual, and trustworthy multi-turn dialog. Join us, and we will take on the challenges to push the frontiers of foundation models and conversational AI!

MSc in Computer Science, Machine Learning, Statistics, or a related field\nProven experience in machine learning or a related engineering role\nStrong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX)\nExperience with the full ML lifecycle: data processing, training, evaluation, deployment\nFamiliarity with distributed training and large-scale data pipelines\nSolid understanding of ML fundamentals: supervised/unsupervised learning, model evaluation, regularization\nExperience with cloud platforms (AWS, Google Cloud Platform, or Azure) and containerization (Docker, Kubernetes)\nStrong software engineering practices: testing, code review, version control

PhD in Machine Learning, Computer Science, or a related field\nExperience with LLMs, pre-training, fine-tuning, RL\nFamiliarity with MLOps tools (MLflow, Weights & Biases, Kubeflow)\nBackground in a specific domain (audio generation, speech-to-speech, NLP)\nExperience with real-time serving infrastructure
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: 8c293573418c982fd09400b933a49be2
  • Posted 4 hours ago
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