Apple is looking to build the platform that enables the next generation of intelligent experiences on Apple products & services, specifically focusing on designing and building critical services that support Apple Intelligence, machine learning and computer vision efforts across the company.
Requirements
- Strong software development skills, proficiency in relevant languages (e.g. Python)
- Experience designing and building services and APIs, especially micro-services
- Familiarity with relational database systems such as PostgreSQL, and experience with distributed systems and services
- Proficiency with CI/CD, Container orchestration technologies like Kubernetes & EC2
- Experience using system monitoring tools and automated testing frameworks
- Experience delivering distributed systems and services in a production setting
- Experience with Kubernetes and cloud infrastructure
Responsibilities
- Lead the architecture, design, development, and operations of systems designed for running machine learning workloads across all of Apple’s platforms and devices.
- These may include, but not limited to data management systems, engineering workflow systems, distributed compute systems and user-facing UIs and APIs.
- Partner with various teams and machine learning engineers across different Apple organizations to define high impact product features and deliver them with quality.
- In this role you will be working on core infrastructure that teams across the company leverage to deliver ML powered products and features.
- Lead a group of engineers to deliver high quality products/services.
- Be able to stay on top of innovative technologies and apply them in the job.
- Support junior engineers by providing advice, coaching and educational opportunities.
Other
- Obsessed with the end user experience; previous experience in taking a product from design & inception to production
- 5 years of industry experience in software development
- BS in Computer Science or equivalent industry work experience
- Experience with Machine Learning and ML lifecycle / deployment
- Master or PhD in Computer Science or equivalent industry work experience
