Senior Engineering Manager, Apple Data Platform

We are looking for a Senior Engineering Manager to lead the team building foundational systems and services that power Apples AI and Data governance platform. This role sits at the intersection of Big Data management ML infrastructure 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 enable governance of large scale data-lakes and GenAI infrastructure spanning the entire GenAI model development lifecycle. Your work will ensure compliance with the latest AI regulations while accelerating AI/ML development and experimentation. You will directly influence how ML practitioners develop and scale models across a wide range of products and services within Apple.n

As a Senior Engineering Manager in the AI and Data Governance group you will lead the design and delivery of core systems and services that enable governance of Apples data management and machine learning solutions spanning the full ML lifecycle from experimentation to large-scale training and 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 Legal Compliance ML engineers 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 Governance Big Data and AI with an experience of building world-class platforms at scale and comfortable operating across diverse infrastructure environments. This is a unique opportunity to shape how data and machine learning is developed deployed and governed at scale within Apple with the autonomy to experiment the scale to make meaningful impact and the support to take ideas from concept to production.n

Lead mentor and grow a high-performing team of software engineers and technical and communicate a clear long-term technical vision aligned with business priorities and guide short- and mid-term execution toward that the design delivery and operation of large-scale data and AI governance closely with Legal Compliance ML engineers data scientists researchers and cross-functional stakeholders to define high-impact capabilities and deliver them with quality and reliability scalability and operational excellence including defining success metrics and continuously improving availability and complex cross-team dependencies and influence without direct authority to drive alignment and a strong engineering culture that values technical excellence collaboration accountability and continuous closely with recruiting to attract and retain top-tier engineering talent and build a diverse inclusive the organizations technical direction and progress to senior leadership and key stakeholders.n

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 understanding of governance and compliance trends and regulations for data and experience delivering large-scale distributed systems and ML/data infrastructure into production track record of leading mentoring and scaling high-performing infrastructure and platform passion for building reliable scalable systems with high availability strong performance and an excellent developer navigating complex cross-functional environments and managing expectations across multiple stakeholders and partner communication skills with the ability to clearly articulate technical strategy trade-offs and impact to diverse audiences including senior ability to partner effectively with recruiting to attract assess and grow top technical business acumen and results-driven mindset with the ability to balance long-term strategic investments with near-term operating in ambiguity taking initiative and leading teams through fast-paced evolving problem .S. M.S. or Ph.D. in Computer Science Computer Engineering or equivalent practical experience.n

Experience building platforms that enable Data/AI governance and/or Responsible AI at designing or operating high-performance data access paths for ML training and supervised working with ML practitioners data scientists and researchers to translate research needs into scalable production operating ML Ops infrastructure across heterogeneous environments including on-prem hybrid or multi-cloud perspective on where ML platforms and AI infrastructure are headed and the ability to adapt platform strategy as the ecosystem evolve.n