StaffSenior Machine Learning Engineer, Search & Knowledge Platforms

The AI Search u0026 Knowledge Platforms team builds amazing products and services for Apples customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI search and knowledge systems powering Siri Apple Intelligence Safari and iMessage and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale. As part of this group you will focus on identifying and addressing opportunities to improve the quality and performance of the search and ranking stack that powers world knowledge question answering. This involves developing sophisticated machine learning systems robust software heuristics and large language models (LLMs) to understand user queries retrieve and rank relevant documents and provide users with direct answers that best satisfy their intent. You will work across the entire stack applying a broad skill set that ranges from data science and opportunity analysis to ML system design pipeline development and quality evaluation.

As a member of our fast-paced group you will have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for a highly motivated and versatile Machine Learning and Software Engineer with a broad skill set. The ideal candidate combines strong engineering fundamentals with a keen product sense and is a quick learner who is comfortable jumping into entirely new codebases and architectures. You must be an effective communicator and an adaptable problem solver willing to take on whatever represents the optimal solution for the product whether that means training machine learning models writing robust software heuristics or iterating on prompt engineering.

Identify and address opportunities to improve the quality and performance of the search and ranking stack that powers world knowledge question product requirements and apply a keen product sense to design engineering solutions that directly reflect our product reliable scalable ways to measure assess and compare the impact of different solutions on system quality and a versatile skill set encompassing data science opportunity analysis ML system design pipeline development and quality and contribute effectively to entirely new codebases and complex findings clearly to cross-functional teams and leadership backing up recommendations with solid rigorous data quickly and adapt to the best technical approach for any given problem seamlessly shifting between ML model training software engineering and prompt engineering.

Bachelors in Computer Science Artificial Intelligence Machine Learning or a related field.n6 years experience in shipping Search and ML systemsnStrong programming skills in Python Go or similar languages with a solid foundation in software design data structures and building scalable data pipelines and backend systems coupled with the ability to quickly navigate and contribute to large complex and unfamiliar in data science methodologies including A/B testing statistical hypothesis testing and defining offline and online evaluation metrics for ML with prompt engineeringnStrong product sense with the ability to translate ambiguous product requirements into concrete engineering and modeling communication skills with the ability to back up decisions with rigorous data analysis and present findings clearly to cross-functional partners.

Masters/Ph.D in Computer Science Artificial Intelligence Machine Learning or a related field.n4 years experience in shipping Search and ML systemsnHands-on experience in Information Retrieval Search Ranking or Natural Language Processing (NLP).nDemonstrated experience designing building or working with Retrieval-Augmented Generation (RAG) architectures and with techniques for optimizing the inference performance latency and resource efficiency of LLMs and large machine learning systems in production environments (e.g. model quantization caching distributed inference).nExperience with training and deploying machine learning models