Senior Machine Learning Engineer, Natural Language Generation

From our origins in iPhone keyboard input, the Input Experience NLP team has expanded to a broad charter: improve the user experience with robust language understanding and personalized text composition, across languages and Apple platforms. We build the ML models that underlie Summarization, Smart Reply, Writing Tools, and other features deeply integrated into Apple products. Generative AI is a transformative technology that we have only just begun to incorporate into our digital lives, to help everyday people digest the deluge of information they receive and express themselves more clearly. On our team, you will help build the future and have a voice in the shape it takes., We are looking for a Senior Machine Learning Engineer to own the model quality of Summarization and other core Apple Intelligence features. You will develop the next generation of our ML models, so that they better serve the full range of our customers, across languages, writing styles, and other personal context, in a privacy-preserving way and to Apple’s high standards of quality. You will design the architecture of the modeling pipelines that define our slice of Apple Intelligence, driving the direction of our team’s efforts to produce user experiences that feel magical. You will join an ambitious, organized, and collaborative team. We’re in a unique position to integrate the latest innovations from the ML community and work on features that reach everyday users, including your family and friends. You’ll work closely with other teams across Apple, collaborating on human interfaces, user studies, internationalization, ML technologies, system integration, and more., As a Senior Machine Learning Engineer on our team, you will be responsible for the definition, design, and quality of increasingly sophisticated AI features that ship to a global audience. You will drive the development of workflows that facilitate efficient data synthesis, data curation, prompt engineering, and model evaluation. Finally, you will contribute to a company-wide effort to build robust modeling processes that optimize our ability to iterate rapidly and continuously deliver improvements to our customers., * Own the model quality of shipping and unreleased Apple Intelligence features

• Prioritize and drive modeling efforts across multiple fronts
• Analyze user feedback to understand shortcomings of our models and evaluation data
• Define robust evaluation mechanisms to drive data curation, metric calibration, and model hill-climbing
• Research state-of-the-art SFT/PEFT/RLHF/distillation techniques for improving model quality and robustness
• Implement pipelines, experiments, and simulations to assess the value of modeling changes

• MS or PhD in Computer Science or related field, or equivalent practical experience
• History of shipping AI features built on language models
• Experience building and maintaining model pipelines end-to-end, from data curation/synthesis and LLM judges to post-training
• Strong Python programming skills, with experience developing production-quality Python modules
• Excellent written and verbal communication skills, * History of driving cross-functional collaborations and leading technical efforts
• Expertise deploying models on-device, reasoning about latency, activation size, quantization, and distillation
• Background in linguistics, fluency in multiple languages, or experience scaling NLP features for global audiences

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something-you’ll add something.