Apple Ray Inference Engineer

Job Description

The Apple Data Platform (ADP) group is looking for an experienced engineer passionate about machine learning, infrastructure, big data, and distributed systems to build and serve world-class data+ML platforms/products at scale.

Requirements

• 5+ years of experience in distributed systems with deep knowledge in computer science fundamentals
• Experience managing deployments of LLMs at scale
• Experience with ML Training/Inference profiling and optimization for different workloads and tasks
• Experience with containerization and orchestration technologies, such as Docker and Kubernetes
• Extensive programming experience in Java, Python or Go
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience

Responsibilities

• Designing, implementing, and maintaining distributed systems to build world-class ML platforms/products at scale
• Experiment with, deploy, and manage LLMs in a production context
• Benchmark and optimize inference deployments for different workloads
• Diagnose, fix, improve, and automate complex issues across the entire stack
• Design and extend services to improve functionality and reliability of the platform
• Monitor system performance, optimize for cost and efficiency, and resolve any issues that arise
• Build relationships with stakeholders across the organization to better understand internal customer needs and enhance the product for end users

Benefits

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.