Senior / Staff Software Engineer, Apple Data Platform at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

08 Apr, 26

Salary

0.0

Posted On

08 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Large-Scale Scheduling, Orchestration, Data Workloads, AI Workloads, Kubernetes, Cloud-Native Infrastructure, Multi-Cloud Environments, AWS, GCP, Cluster-Scheduling Technologies, GPU Scheduling, Distributed Systems, Observability, Scalability, Reliability, Mentoring

Industry

Computers and Electronics Manufacturing

Description

The Apple Data Platform team powers the data analytics, exploration, and feature engineering that fuel Siri, Search, Music, Maps, iCloud, and many other beloved products across the Apple ecosystem. Our mission is to provide engineers and data scientists with an innovative, reliable, secure, and user-friendly platform for ingesting, storing, processing, and interacting with data—ultimately enabling teams to derive insights that drive product success. Apple Batch is a fully managed platform within the Apple Data Platform that supports large-scale batch and ML workloads across Apple data centers and AWS/GCP. It orchestrates containerized workloads such as Spark, Ray, and LLM batch inference using YuniKorn/Kueue for advanced multi-cluster scheduling. The platform delivers org/team quota management, automatic node repair, end-to-end observability, strong security, and granular cost reporting. As we scale Apple Batch across all Data and AI services and Apple-wide ADP customers, we are seeking a Staff/Architect-level technical lead to shape its evolution and drive platform adoption across the company. DESCRIPTION Apple Batch, a core platform within the Apple Data/AI ecosystem, enables large-scale scheduling, orchestration, efficiency, and observability for AI and Data workloads across Apple data centers and public cloud providers. We are looking for a Staff/Architect-level technical lead to drive the next generation of the platform and scale it across all Data and AI services and Apple-wide ADP customers. MINIMUM QUALIFICATIONS Demonstrated expertise in large-scale scheduling/orchestration for Data and AI workloads on Kubernetes, Slurm, or similar platforms. Strong proficiency with cloud-native infrastructure across multi-cloud environments including AWS, GCP, and on-prem systems. Deep knowledge of cluster-scheduling technologies such as Kueue, Apache YuniKorn, or related ecosystems. Experience or strong knowledge in GPU scheduling, accelerator-aware placement, and optimization algorithms for large-scale AI/ML workloads. Proven experience designing and operating large-scale distributed systems with a deep focus on observability, scalability, and reliability. Demonstrated ability to mentor engineers, influence architectural direction, drive cross-functional alignment, and lead complex platform migrations or adoption at org-wide scale. Bachelors/Masters/PhD in Computer Science or related field. PREFERRED QUALIFICATIONS Open-source contributions to scheduling/orchestration technologies such as Apache YuniKorn, Kueue, or similar systems. Experience using GenAI technologies to improve developer productivity, streamline engineering processes, and accelerate team execution.

Responsibilities

Drive the evolution of the Apple Batch platform and scale it across all Data and AI services. Lead the adoption of the platform across the company.