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Description
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!
Minimum Qualifications
MSc in Computer Science, Machine Learning, Statistics, or a related field Proven experience in machine learning or a related engineering role Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX) Experience with the full ML lifecycle: data processing, training, evaluation, deployment Familiarity with distributed training and large-scale data pipelines Solid understanding of ML fundamentals: supervised/unsupervised learning, model evaluation, regularization Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) Strong software engineering practices: testing, code review, version control
Preferred Qualifications
PhD in Machine Learning, Computer Science, or a related field Experience with LLMs, pre-training, fine-tuning, RL Familiarity with MLOps tools (MLflow, Weights & Biases, Kubeflow) Background in a specific domain (audio generation, speech-to-speech, NLP) Experience with real-time serving infrastructure
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