Summary
The ASE Search team is looking for Machine Learning Researchers and Engineers to develop next-generation search and conversational discovery features for Apple's platforms. This role involves building large-scale ML & data systems, with a focus on generative AI, Large Language Models, and distributed training frameworks. Requires 3+ years of experience, strong knowledge of ML concepts, and leadership skills. Opportunities to work on App Store, Apple Music, and more.
Description
The ASE Search team is a vital part of Apple ecosystem, powering search for App Store, Apple Music, Apple TV, Podcasts, Books, iTunes and more, on a wide set of platforms such as iOS, macOS, tvOS, watchOS, Safari, and 3rd party devices. Driven by passion for the extraordinary rather than the easy, our team of problem solvers, is dedicated to helping users discover media and content in exciting new ways. We are looking for extraordinary and motivated machine learning researchers and engineers to join us in our journey. As a Senior/Staff Machine Learning Research on the ASE Search team, you will lead the design and development of next-generation search and conversational discovery features for Apple's ground breaking devices and platforms.
3+ years of relevant industry experience building large-scale ML & data systems
Familiarity with search or recommendation systems, conversational engines, or related domains
Strong knowledge of generative AI systems including Large Language Models, Transformers, Reinforcement Learning, RAG, and agentic patterns such as ReAct, Chain-of-Thought, Tool Use, and Multi-Agent orchestration
Experience with one or more distributed ML training frameworks such as PyTorch, TensorFlow, Ray, or JAX, and inference engines like TensorRT or vLLM
Technical leader with exceptional communication skills and a track record of solving complex, ambiguous problems in a highly collaborative environment
MS or Ph.D. in Computer Science or related subject area
Proven ability to build & scale Search & Conversational systems, applying 7+ years of hand-on experience across the full product stack — including query understanding, semantic retrieval, multi-stage ranking, indexing, intent classification, and context-aware generation.
Deep expertise in Search & Conversational systems, bringing in 7+ years of hands-on experience building capabilities such as query understanding, retrieval, ranking, indexing, autocomplete, intent resolution, and context-aware generation across multiple domains.
Proficient in developing robust big data pipelines in Scala or Python using distributed processing frameworks like Apache Spark.
Familiarity with scalable, reliable distributed backend services including Kubernetes, cloud infrastructure, and container orchestration
Familiarity with A/B experimentation and data-driven product development
