Apple

Summary

Posted: May 29, 2026

Weekly Hours: 40

Role Number:200665146

The Applied Machine Learning team has been at the forefront of accelerating digital transformation through machine learning across Apple's enterprise ecosystem. The proven ML Platforms, Solutions, and Services provide a comprehensive suite of capabilities to achieve efficiency, agility, and innovation at Apple scale—serving business-critical needs across Apple’s enterprise. We are seeking a highly motivated and skilled Engineering Manager to lead and scale the Search / Information Retrieval team. The ideal candidate will have a strong foundation in Java development, a solid understanding of distributed systems, hands-on experience in Search, Information Retrieval and relevancy tuning, and a keen interest in Generative AI (GenAI). You will play a critical role in building, scaling, and maintaining next-generation systems and applications that leverage the power of Search & GenAI technologies, ensuring robust, scalable, and efficient solutions.

Description

Embark on a transformative journey as an Engineering Manager within Apple's Applied Machine Learning Team. In this role, you will be responsible for the strategic direction, technical architecture, and leadership of a high-performing engineering team. You will assume a pivotal role in building and supporting the high-performance, scalable enterprise platforms that underpin our Search, Knowledge Graph, ML and inferencing systems. You shall be entrusted with the stewardship of ensuring unparalleled availability, optimal performance, and minimal latency for our high-throughput applications, thereby directly influencing and elevating the customer experience. Your responsibilities will encompass the development and optimal functioning of diverse workloads across ML/KG/Inference platforms, coupled with the exploration of, and building deep understanding of latest open source technologies and innovative solutions. You will bridge the gap between legacy search infrastructure (IR) and modern Generative AI capabilities to build next-generation, highly intelligent information ecosystems. A proven aptitude for outstanding interpersonal communication, a high degree of accountability and the capacity to collaborate seamlessly across multifaceted business and technical teams are paramount.

Minimum Qualifications

• Bachelor’s Degree in Computer Science, Information Technology or equivalent.
• 10+ Years of experience in Software Engineering, with at least 3+ years in a leadership or management capacity.
• Proficiency in Java and in Information Retrieval and Generative AI.

Preferred Qualifications

• Deep Expertise in Search & IR - Strong understanding of classic Information Retrieval algorithms, relevance tuning, and ranking architectures (e.g. Solr, Open Search, Lucene).
• Proven track record of designing systems that integrate Generative AI, RAG (Retrieval-Augmented Generation), Vector Databases, and Hybrid Search strategies.
• Advanced Proficiency in Java & either Information Retrieval or Generative AI
• Proven history of designing, architecting, and deploying highly available, distributed systems capable of handling massive data volumes and low-latency requirements.
• Strong understanding of software engineering principles and fundamentals including data structures and algorithms.
• Demonstrated ability to build, hire, and retain top-tier engineering talent. Experience managing teams of engineers across various skill levels (Junior to Senior).
• Excellent ability to manage expectations and communication between executives, Product Managers, and cross-functional teams
• Solid understanding of concurrency and multi-threading, multiple design patterns and debugging and analytical methodologies
• Exposure to Data processing and Model Training or FineTuning methodologies
• Exposure to Performance tuning JVMs
• Exposure to BigData processing systems
• Meaningful Contributions to OpenSource Software
• Ability to foster a culture of innovation, psychological safety, and technical excellence within a fast-paced environment.

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