Senior Engineering Manager, Apple Data Platform
Apple
Software Engineering, Other Engineering
Cupertino, CA, USA
USD 181,100-318,400 / year + Equity
Posted on Dec 18, 2025
We are looking for a Senior Engineering Manager to lead teams building foundational platforms that power large-scale machine learning. This role sits at the intersection of ML infrastructure, data-centric ML, and generative AI, enabling teams across the company to move from data to trained models efficiently, reliably, and at scale. You will lead efforts that unify ML dataset creation and sharing with built-in governance, accelerate model quality through intelligent data workflows, and deliver high-performance data access for training and experimentation. Your work will directly influence how ML practitioners develop, optimize, and scale models across a wide range of products and services. You will join a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent experiences on Apple products and services.
As a Senior Engineering Manager in the ML Data group, you will lead the design and delivery of core platforms that support the full ML lifecycle, from experimentation to large-scale training and deployment. These platforms enable teams to create and share ML datasets with governance provided out of the box, improve training outcomes through data-centric capabilities such as synthetic data generation, rapid data transformation, and visualization, and efficiently load data at scale for modern accelerators. Your teams will build and operate systems that support multimodal data, including text, images, audio, and more, while ensuring data access remains efficient and predictable as workloads grow. This includes designing and scaling high-performance data paths that support streaming, random access, sharding, and high-throughput sequential reads to keep training pipelines performant and GPUs fully utilized. This role requires strong leadership in infrastructure and distributed systems, paired with strategic thinking and effective execution in complex, cross-functional environments. You will work closely with ML researchers, platform and infrastructure teams, and product partners to align on requirements, set technical direction, and deliver multi-quarter initiatives with broad organizational impact. We are looking for an experienced leader who is passionate about building world-class ML platforms at scale, comfortable operating across diverse infrastructure environments, and excited to work at the intersection of cutting-edge ML research and production systems. This is a unique opportunity to shape how machine learning is developed, deployed, and scaled across the company, with the autonomy to experiment, the scale to make meaningful impact, and the support to take ideas from concept to production.
- Lead, mentor, and grow a high-performing organization of software engineers, technical leads, and engineering managers.
- Set and communicate a clear long-term technical vision aligned with business priorities, and guide short- and mid-term execution toward that vision.
- Drive the design, delivery, and operation of large-scale ML data and infrastructure platforms that support the full ML lifecycle.
- Partner closely with ML engineers, data scientists, researchers, and cross-functional stakeholders to define high-impact capabilities and deliver them with quality and reliability.
- Own reliability, scalability, and operational excellence, including defining success metrics and continuously improving availability and performance.
- Navigate complex cross-team dependencies and influence without direct authority to drive alignment and execution.
- Foster a strong engineering culture that values technical excellence, collaboration, accountability, and continuous improvement.
- Work closely with recruiting to attract and retain top-tier engineering talent and build a diverse, inclusive team.
- Represent the organization’s technical direction and progress to senior leadership and key stakeholders.
- Proven ability to define and execute a forward-looking technical vision, with a strong understanding of emerging trends in AI, generative models, and data-centric machine learning.
- Demonstrated experience delivering large-scale distributed systems and ML/data infrastructure into production environments.
- Strong track record of leading, mentoring, and scaling high-performing infrastructure and platform teams.
- Deep passion for building reliable, scalable systems with high availability, strong performance, and an excellent developer experience.
- Experience navigating complex, cross-functional environments and managing expectations across multiple stakeholders and partner teams.
- Proven ability to partner effectively with recruiting to attract, assess, and grow top technical Excellent communication skills, with the ability to clearly articulate technical strategy, trade-offs, and impact to diverse audiences, including senior leadership.
- Strong business acumen and results-driven mindset, with the ability to balance long-term strategic investments with near-term delivery.
- Comfortable operating in ambiguity, taking initiative, and leading teams through fast-paced, evolving problem spaces.
- B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience
- Experience leading platforms that support data-centric ML, foundation models, or generative AI workloads at scale.
- Familiarity with multimodal data systems spanning text, images, audio, video, and embeddings.
- Experience designing or operating high-performance data access paths for ML training, including streaming, sharding, random access, and large-scale sequential reads.
- Background working with ML practitioners, data scientists, and researchers to translate research needs into scalable production systems.
- Experience operating ML infrastructure across heterogeneous environments, including on-prem, hybrid, or multi-cloud deployments.
- Exposure to governance, lineage, and compliance considerations in large-scale data and ML platforms.
- Strong perspective on where ML platforms and AI infrastructure are headed, and the ability to adapt platform strategy as the ecosystem evolve
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.