About the position
Apple Data Platform serves as a foundational building block for Apple's Services, Software, and AI/ML ecosystem, providing advanced data governance, compliance, and scalable data management. It offers a comprehensive suite of capabilities, including batch and real-time data processing, embeddings management, feature stores, lakehouse architecture, data virtualization, and inference as a service. These tools empower analytics and AI workflows across Apple's ecosystem, driving seamless integration and innovation across products and services. Leveraging open-source technologies such as Ray, Spark, Flink, and Iceberg across multi-cloud and on-premises environments, the Apple Data Platform powers data-driven intelligence that continuously enhances the customer experience. We are seeking a Senior Engineering Leader with a passion for delivering scalable, secure, and user-friendly infrastructure for all of Data and AI platforms.
Responsibilities
- Drive the overall strategy and execution of the ADP Compute Platform.
- Collaborate with key stakeholders and partners to deliver integrations, compliance, cost efficiency, and an optimal experience.
- Partner with internal customers and product teams to drive the platform roadmap and accelerate adoption of the platform.
- Lead and mentor a team of engineers, providing guidance, support, and professional development opportunities.
- Cultivate a culture of collaboration, innovation, and continuous learning within the team.
- Identify opportunities and drive a strategic approach to contributing to open source.
Requirements
- 12+ years of software development experience in Data and AI platforms and infrastructure.
- 8+ years of engineering people management experience-leading, mentoring, and growing teams.
- 10+ years of experience building and operationalizing data platform technologies on AWS, Azure, GCP, and on-premises infrastructures.
- Strong leadership in cross-functional collaboration, driving alignment across engineering, product, and business teams to accelerate platform adoption.
- Expertise in distributed systems and cloud-native infrastructure, including Kubernetes, serverless computing, and container orchestration.
- Experience designing and optimizing large-scale compute platforms with advanced scheduling, resource management, and cost efficiency considerations.
- BS, MS, or Ph.D. in Computer Science or a related field of study.
Nice-to-haves
- Expertise in AI/ML workload orchestration and scheduling, including optimizing resource allocation for large-scale training, inference, and data processing pipelines.
- Experience building and managing AI infrastructure platforms, integrating frameworks like TensorFlow, PyTorch, Ray, and Spark with distributed compute environments.
- Deep understanding of AI cost efficiency and performance optimization, leveraging techniques such as model parallelism, heterogeneous compute scheduling (GPUs, TPUs), and auto-scaling for AI workloads.
Benefits
- Comprehensive medical and dental coverage
- Retirement benefits
- A range of discounted products and free services
- Reimbursement for certain educational expenses - including tuition
- Discretionary bonuses or commission payments
- Relocation assistance
- Opportunity to participate in Apple's discretionary employee stock programs
