Machine Learning Engineer, Search & Knowledge Quality

The Search and Knowledge Quality team is redefining how hundreds of millions of users interact with their devices to access information. We are an Applied Machine Learning team pushing the boundaries of artificial intelligence-from query understanding and information retrieval to response ranking and contextual answer generation.\\n\\nOur team drives innovation by conducting research, building end-to-end solutions, and deploying them at scale to deliver meaningful customer impact across Apple products.\\n\\nIn this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale.

In this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale.

BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field.\n3+ years of industry related experience, working in collaborate environments\nExperience with programming skills in Python,C/C++, GoLand\nExperience with ML libraries such as TensorFlow, PyTorch, HuggingFace, AXLearn and Scikit-learn.\nFamiliarity with integrating ML solutions into production systems and existing workflows at scale; experience with CI/CD workflows and ML pipelines .\nExcellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences.\nStrong problem-solving skills and ability to work independently as well as in a team environment.

Ph.D. in a related field.\nExperience with state-of-the-art ML methodologies, including LLM fine-tuning, neural network optimization , RL\nStrong communication and accountability skills; a hard-working, strong work ethic, and collaboration abilities.\nExperimental rigor when training/evaluating LLMs for the purpose of benchmarking LLM optimization algorithms.