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!","responsibilities":"Design, train, and evaluate machine learning models for production use cases
Build and maintain scalable ML pipelines (data ingestion, feature engineering, training, evaluation, serving)
Collaborate with data scientists to translate research prototypes into robust, production-grade systems
Monitor deployed models for performance degradation and data drift
Optimize models for latency, throughput, and resource efficiency
Contribute to ML infrastructure, tooling, and best practices
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
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","internalDetails":null
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.