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Sr. Machine Learning Engineer, Siri Speech

**Weekly Hours:** 40

**Role Number:** 200662258-0836

**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!

**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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