The ACAI Training & Inference Platform team is looking for a Senior / Staff Software Engineer with expertise in distributed systems and AI training and inference. This role involves designing and building capabilities for large-scale model training, fine-tuning, and high-performance inference within Apple's AI ecosystem. The engineer will work closely with AI researchers to translate model architectures into efficient training and inference solutions. The ideal candidate will have a strong background in modern LLM training and optimization.

• 6+ years of experience building distributed systems, AI platforms, or high-performance software systems.
• Strong hands-on experience in large-scale AI training, LLM post-training, or LLM inference optimization.
• Proficiency in Python and experience with a systems-level language such as C++, Rust, Go, or Java.
• Experience with PyTorch and modern foundation model architectures.
• Understanding of distributed execution and parallelism strategies for large models.
• Experience profiling and optimizing AI workloads across GPUs or other accelerators.
• Strong understanding of distributed training and post-training workflows.
• Experience building APIs, SDKs, or reusable software components for AI model development.
• Experience with Ray or comparable distributed execution frameworks.
• Strong software design, debugging, and performance analysis skills.
• B.S., M.S., or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.

• Design and build core capabilities for large-scale model training and inference.
• Develop scalable AI execution frameworks and developer-facing APIs.
• Partner with AI researchers to translate model architectures into efficient solutions.
• Simplify the execution of complex training pipelines and improve iteration speed.
• Drive runtime and LLM-serving optimizations to enhance throughput and reduce latency.
• Identify bottlenecks in model execution and translate insights into improvements.
• Integrate training and inference engines into production AI platforms.
• Contribute to open-source AI training and inference projects.
• Operate AI workloads in production across cloud or on-premises environments.

• 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.