Data and Applied AI Engineer

Imagine what you could do here. At Apple new ideas have a way of becoming extraordinary products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you can accomplish. Would you like the stimulation and challenges of building world-class extraordinary scalable systems that power App Store Music TV Fitness Arcade and many more Then this is the opportunity for you at Apple! We strive to provide a flawless experience for millions of customers and are seeking a Software Engineer to join Apple Services Engineering (ASE) who brings deep passion for building distributed large scale data processing systems frameworks and platforms using big data technologies. You will partner with Apple TV and Video teams and work collaboratively to make a significant impact on Apple TV customers.n

Data is our first class citizen. The volume of the data is on petabyte scale and we are software engineers who build distributed systems to generate data analytics. The systems should scale well be highly available and provide consistent results. The systems we build have significant impact on our stakeholders and partners who use the data for business insights. We are deeply committed to Apples privacy policy which forms Apples core values. You will have important responsibility and influence in designing and building the data platform to empower data analytics and delivering the solutions that have significant impact on Apple TV and Sports products. nnn* An ideal candidate will collaborate with our partner teams to design and implement data solutions to support the business needs. We are looking for someone with a love for data and ability to iterate quickly on all stages of data pipelines. n* This position involves working on a small team to develop large scale data pipelines and backend services using microservices and big data technologies. n* Successful candidates will have strong AI engineering and communication skills. n* The ideal candidate has a real passion for quality and an ability to understand complex systems. If this sounds like you then we would love to hear from

Develop Distributed Data Processing Systems: Design and build scalable highly available distributed systems for large-scale data processing and analytics ensuring consistent results and significant impact on with TV and Video Teams: Partner with Apple TV and Video teams to develop and enhance data platforms delivering solutions that significantly impact Apple TV and Sports AI for Automation: Leverage AI to develop agents that help in automating routine work and provide new capabilities for and Develop Microservices: Create and maintain backend services using microservices architecture and big data technologies supporting large-scale data and Translate Requirements: Gather cross-functional requirements and translate them into practical engineering tasks ensuring alignment with project goals and Architecture and Design Documents: Develop detailed architecture and design documentation guiding the engineering team in building robust and scalable data processing Data Privacy Compliance: Uphold Apples core values by ensuring all systems and solutions comply with Apples privacy policy maintaining data security and privacy and Improve Code Quality: Demonstrate a passion for quality by understanding complex systems writing clean efficient code and continuously improving the software engineering process.

3 years of programming experience in Java or or Masters degree in Computer Science Mathematics or equivalent technical discipline and experience working with large scale distributed data processing technologies and developing AI in working with big data and distributed developing microservices and REST working with LLMs and developing AI u0026 build LLM-powered applications and intelligent agents at scale

Good understanding of software engineering principles and fundamentals including algorithms and data structures. nSelf-directed self-motivated and able to create architecture and design to capture cross-functional requirements and translate them into practical engineering tasks.