Applied LLM Research Engineer, Input Experience

From our origins in iPhone keyboard input the Input Experience NLP team has expanded our broad charter: enhancing the user experience with robust language understanding and personalized text composition across all Apple platforms and languages. Generative AI is a transformative technology and we are just beginning to harness its potential to help users digest information and express themselves more clearly. On our team you will help build the future and shape its evolution. Our work has been featured in multiple WWDC keynotes including Intelligent Input in 2023 Writing Tools Summarization Smart Reply as part of Apple Intelligence in 2024! Building on years of innovation in intelligent systems and on-device machine learning we are now scaling efforts in bringing powerful foundation models directly into everyday are looking for Applied LLM Research Engineer to innovate and develop technology that brings powerful foundation models directly into everyday user workflows across languages writing styles and personal context in a privacy-preserving way. You will build run and refine the training and evaluation pipelines that define our slice of Apple Intelligence driving the experimentation and iteration that makes the user experience feel magical. You will join an ambitious collaborative team in a unique position to bridge the gap between cutting-edge ML research and features used by millions. You will work closely with cross-functional partners in human interfaces user studies internationalization and system integration. You are not just developing technology; you are crafting experiences that feel like magic to the end 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 others 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. Its 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 youll do more than join somethingyoull add something.

As an Applied LLM Research Engineer you will enable next-generation AI applications using Apple Foundation Models. You will sit at the intersection of cutting-edge research and product reality bridging the gap between raw model performance and the nuanced needs of Apple customers worldwide. You will explore design and implement emerging techniques ensuring alignment with product goals privacy requirements and performance metrics. You will contribute to all phases of model development: problem formulation experimentation evaluation fine-tuning and continuous improvement. Finally you will help define and refine new features that expand both the depth of Apple Intelligences capabilities and the breadth of its support for our global customer base.

PhD in CS/EE/Physics/Statistics/etc.; or Bachelors or Masters in CS/EE/Physics/Statistics/etc combined with 2 years of relevant experiencenStrong foundations in ML u0026 LLM including core principles techniques and practical applicationsnFamiliarity with post-training techniques such as SFT RLHF data synthesis Parameter-Efficient Fine-TuningnFamiliarity with training frameworks such as PyTorch JAX TensorFlow or equivalent

Experience with fine-tuning and deploying large ML models for real world productsnExperience curating filtering and synthesizing high-quality training datasets at scalenExperience developing and training models for agentic workflows tool calling and advanced reasoning techniquesnExperience with training LLMs with RLVR reward modeling environment designnFamiliarity with training for computer-use capabilitiesnFamiliarity with designing hardware-efficient model architectures optimizing inference latency and implementing advanced decoding strategies speculative decodingnActive contributor to complex large-scale codebases with a strong emphasis on writing high-quality maintainable and well-tested using AI-assisted development tools (e.g. Claude Copilot or similar) to accelerate experimentation code development and research workflowsnExcellent programming and communication skills