AIML - Senior Engineering Manager, Summarization
Apple
Software Engineering, Other Engineering
Cupertino, CA, USA
USD 219,300-378,700 / year + Equity
Posted on Mar 27, 2025
Summary
Posted:
Role Number:200594748
Apple is where individual imaginations gather together, contributing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience, we deliver results by strengthening each other’s ideas. That happens because we believe we can make something wonderful and share it with the world, changing lives for the better! Here, you’ll do more than join something — you’ll add something. In the Siri and Information Intelligence organization, we work hard to bring the best user experiences powered by Apple Intelligence. One integral part of the user experience is providing customizable summaries for Apple users’ multiple content consumption for both on-device personal content and on-server world knowledge in Siri, Safari, and many other 1P and 3P Apps in Apple’s ecosystem across different platforms. This means generating accurate, concise, grounded summaries of notifications, messages, emails, documents, web answers, etc, in rich and intuitive experiences. Create ground-breaking Generative AI technology to enable fast, actionable summaries on all devices for all Apps. You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient and effective Generative AI models to build and improve the summarization capabilities across different data types.
Description
Drive E2E R&D and engineering to generate high-quality summaries and experiences for Apple users. This includes on-device LLM models for personal content summarization across 1P and 3P apps, and powerful summarization models on Apple’s Private Cloud Compute servers. In addition, improve the summarization models’ quality for world knowledge-seeking questions and Safari pages to provide accurate answers and highlight web page gists in real-time. Lead the team to develop SOTA LLM-based generative models, groundedness models, and safety models for accurate, grounded, concise, and safe summaries. Develop sophisticated on-device and on-server software frameworks for context integration fast and cost-efficient LLM-based model inference. Integrate the Apple ecosystem with Apple’s LLM infrastructure and generative models to deliver delightful user experiences. Devise the product vision and strategy and execute the plan to deliver the highest quality end-user experience. Collaborate with various organizational partners to profoundly impact billions of Apple users worldwide.
Minimum Qualifications
- 5+ years of experience in leading engineering/applied research/ML experiences in natural language processing, SOTA generative AI models
- Proven record of consistent delivery of technology/products across the full Machine Learning life cycle
- MS or Ph.D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field
Key Qualifications
Preferred Qualifications
- Strong background and experience in Machine Learning, NLP, and RAG.
- Strong engineering and R&D experience in LLM post-training, advanced RL-based methods to improve LLM models’ safety and quality using RLHF/RLAIF, reward model, advanced RL policy optimization algorithms, cutting-edge hallucination reduction methods, and their engineering implementation, hands-on experience to develop and ship RL based models with high availability, low latency, robustness, and stability.
- Exceptional verbal and written communication skills to lead
- Excellent product vision and sound business acumen. Ability to manage long-term strategy and short-term deliverables.
- Strong engineering leadership and fundamentals.
Education & Experience
Additional Requirements
Pay & Benefits
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.