Senior / Staff ML Engineer, Apple Data Platform - Jobs - Careers at Apple
- Design, build, and deploy scalable AI and Data governance and lineage systems that track datasets, models, and policies across Apple's machine learning training and post-training lifecycle.
- Architect and implement authentication and access control frameworks for machine learning training data, model artifacts, and inference endpoints using OAuth 2.0, attribute-based access control (ABAC), and federated identity.
- Develop backend services and distributed applications in Java, Scala, Kotlin, Go, or Python that deeply embed privacy, security, and regulatory requirements such as GDPR, CCPA, and DMA directly into AI and data governance workflows.
- Build batch and streaming pipelines using distributed engines such as Spark, Hadoop, or Flink to transform raw data into governed, machine learning-ready training and inference inputs.
- Design REST APIs, SDKs, and web-based tools using frameworks such as Spring, React, or Node.js that enable internal teams to manage governance approvals and compliance reviews at scale.
- Architect large-scale, fault-tolerant serving systems on AWS, GCP, or Kubernetes that safeguard data integrity, availability, and auditability across Apple's AI governance platforms.
- Collaborate with security, legal, privacy, and data engineering teams to identify and mitigate risk in complex distributed environments, ensuring Apple's AI initiatives set the benchmark for responsible, ethical AI at scale.
- 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.
- 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.
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Required Skills
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🇬🇧 English