苹果Software Engineer (Data), Ai & Data Platforms

We engineer high-quality, scalable and resilient distributed systems on cloud that power data exploration, analytics, reporting and production models. Our core systems are diverse and come with an unusual intersection of high data volumes with systems distributed across cloud and on-premise infrastructure. This role will build solutions that integrate open source software with Apple’s internal ecosystem. You will drive development of new components and features from concept to release: design, build, test, and ship at a regular cadence. You will work closely with internal customers to understand their requirements and workflows, and propose new features and ecosystem changes to streamline their experience of using the solutions on our platform. This is a challenging software engineering role, where a large part of an engineer's time is spent in writing code and designing/developing applications on cloud, with the remainder being spent on tuning and debugging codebase, supporting production applications and supporting our application end users. This role requires in-depth knowledge of innovative technologies and cloud data platform with the ability to independently learn new technologies and contribute to the success of various initiatives.

• Design and implement end-to-end data pipelines (ETL) to ensure efficient data collection, cleansing, transformation, and storage, supporting both real-time and offline analytics needs. • Develop automated data monitoring tools and interactive dashboards to enhance business teams’ insights into core metrics (e.g., user behavior, AI model performance). • Collaborate with cross-functional teams (e.g., Product, Operations, Tech) to align data logic, integrate multi-source data (e.g., user behavior, transaction logs, AI outputs), and build a unified data layer. • Establish data standardization and governance policies to ensure consistency, accuracy, and compliance. • Provide structured data inputs for AI model training and inference (e.g., LLM applications, recommendation systems), optimizing feature engineering workflows. • Explore innovative AI-data integration use cases (e.g., embedding AI-generated insights into BI tools). • Provide technical guidance and best practice on data architecture and BI solution

• MS in Computer Science or equivalent experience • Strong coding skills and experience with data structures and algorithms • Proficiency in one of following languages: Python, Go, Java, C++, Rust • Experience with AWS Services such as Amazon S3 EC2 EKS / Kubernetes • Experience with large scale infrastructure, petabyte scale data processing • Ability to understand/clarify product requirements and translate them into technical tasks

• Develop production-quality software that ships as part of NVIDIA's AI software stack, including optimized large language model (LLM) support. • Analyze the performance of important workloads, tuning our current software, and proposing improvements for future software. • Work with cross-collaborative teams of deep learning software engineers and GPU architects to innovate across applications like generative AI, autonomous driving, computer vision, and recommender systems. • Adapt to the constantly evolving AI industry by being agile and excited to contribute across the codebase, including API design, software architecture, performance modeling, testing, and GPU kernel development.