Machine Learning Engineer - Search & Knowledge Quality

Summary

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. Our team drives innovation by conducting research, building end-to-end solutions, and deploying them at scale to deliver meaningful customer impact across Apple products.

Minimum Qualifications

BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field. 3+ years of industry related experience, working in collaborate environments Experience with programming skills in Python,C/C++, GoLand Experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, AXLearn and Scikit-learn. Familiarity with integrating ML solutions into production systems and existing workflows at scale; experience with CI/CD workflows and ML pipelines . Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences. Strong problem-solving skills and ability to work independently as well as in a team environment.

Preferred Qualifications

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

Description

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.

Responsibilities

Design, develop, and implement machine learning models and RAG based agentic solution for NLP, and multimodal applications. Integrate and own ML solutions into production systems and existing workflows at scale. Collaborate with data scientists, software & ML engineers as well as product managers to define requirements and deliverables Independently own deliverables and apply problem-solving skills to identify solutions to problems to take ownership of complex, ambiguous problems and drive cross-functional solutions with minimal guidance.