Apple is seeking a Staff Software Engineer to design, build, and maintain large-scale distributed systems for AI models and pipelines within their annotation and visualization tools. The goal is to power next-generation AI features and impact millions of users by integrating Generative AI and Large Language Models into Apple's products and services.
Requirements
- Experience in building large scale data processing and distributed systems using technologies like Spark/Kafka
- Experience with cloud platforms such as: AWS, GCP, or Azure
- Experience with SQL / NoSQL databases and embedding data stores
- Proficiency in programming languages such as Python, Java, or Go
- Proven track record of building high-quality, highly scalable backend software systems.
- Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
- Experience with Machine Learning platforms
Responsibilities
- Architect and implement scalable backend systems that support measurement and inference and optimization efforts, ensuring performance and reliability.
- Work closely with data scientists, frontend engineers, product managers, and other stakeholders to define metrics, gather requirements, and deliver impactful solutions.
- Ensure backend services are scalable, efficient, and secure, handling large volumes of data with ease.
- Provide technical leadership and mentorship to junior engineers, fostering a culture of excellence and continuous improvement.
- Deploying and maintaining cloud infrastructure for large-scale data and ML operations.
Other
- Experience leading strategic technical projects with multiple partners and directing work of other engineers or as a technical lead.
- Excellent communication skills and a team-oriented attitude, thriving in a collaborative and fast-paced environment.
- Ability to tackle complex challenges, think critically, and deliver innovative solutions.
- Bachelors in Computer Science, engineering, or a related field
- Advance degrees in Computer Science, engineering, or a related field
