What are the responsibilities and job description for the Senior / Staff ML Engineer, Apple Data Platform position at Apple, Inc.?
As a Senior Software Engineer in Apple AI and Data Governance at Apple, you will be instrumental in designing and implementing robust solutions that ensure the ethical, secure, and compliant use of our data assets and AI systems. In this role, you will leverage your technical expertise to build and maintain frameworks that uphold the integrity, privacy, and security of Apple's AI initiatives while navigating complex regulatory environments. Your work will bridge technical innovation and compliance, ensuring that our AI technologies are responsibly managed throughout their lifecycle.
Description
Are you passionate about building robust, ethical AI and data governance solutions from the ground up? Do you have the vision to tackle the complex challenges of AI data collection, usage, and regulatory compliance? If so, we want you on our team! In this role, you will lead a multidisciplinary team of software engineers to architect Apple's next-generation AI and data governance platforms. You will drive the development of scalable systems that manage the entire machine learning lifecycle - ensuring our AI initiatives set the benchmark for privacy, compliance, and security and are grounded in strong data governance principles. Join us and play a pivotal role in shaping the future of ethical, responsible AI at Apple.
Minimum Qualifications
8 years experience in developing Data & AI governance software or integrating systems with governance systems.
Experience working with large data collection and processing systems.
Demonstrated proficiency in data management and building scalable systems that underpin AI applications.
Strong understanding of privacy and regulatory requirements (e.g., GDPR, CCPA, DMA) and how they apply to Data Governance and AI systems.
Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
Preferred Qualifications
Proven ability to work effectively with diverse teams, including security, legal, privacy, compliance, and data engineering, to drive Data and AI governance initiatives.
Experience in designing and implementing robust data governance frameworks, policies, and standards that ensure the ethical and secure deployment of AI technologies.
A track record of identifying and mitigating risks in complex distributed data environments, with a focus on maintaining compliance in AI-driven projects.
Description
Are you passionate about building robust, ethical AI and data governance solutions from the ground up? Do you have the vision to tackle the complex challenges of AI data collection, usage, and regulatory compliance? If so, we want you on our team! In this role, you will lead a multidisciplinary team of software engineers to architect Apple's next-generation AI and data governance platforms. You will drive the development of scalable systems that manage the entire machine learning lifecycle - ensuring our AI initiatives set the benchmark for privacy, compliance, and security and are grounded in strong data governance principles. Join us and play a pivotal role in shaping the future of ethical, responsible AI at Apple.
Minimum Qualifications
8 years experience in developing Data & AI governance software or integrating systems with governance systems.
Experience working with large data collection and processing systems.
Demonstrated proficiency in data management and building scalable systems that underpin AI applications.
Strong understanding of privacy and regulatory requirements (e.g., GDPR, CCPA, DMA) and how they apply to Data Governance and AI systems.
Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
Preferred Qualifications
Proven ability to work effectively with diverse teams, including security, legal, privacy, compliance, and data engineering, to drive Data and AI governance initiatives.
Experience in designing and implementing robust data governance frameworks, policies, and standards that ensure the ethical and secure deployment of AI technologies.
A track record of identifying and mitigating risks in complex distributed data environments, with a focus on maintaining compliance in AI-driven projects.