Engineering Program Manager, Machine Learning and Data - SIML

$165,500 - $248,700/Yr

Apple - Cupertino, CA

Full-time - Mid Level

Cupertino, CA

Computer and Electronic Product Manufacturing

About the position

As the Engineering Program Manager for the Data Engineering group at Apple, you will play a pivotal role in shaping the future of generative AI and machine learning technologies. The Data Team within the System Intelligence and Machine Learning (SIML) group is responsible for building high-quality ML datasets at scale, which are essential for training machine learning models that power AI-centric features across various Apple products, including iPhone, iPad, Mac, Apple Watch, and AirPods. Your contributions will directly impact critical features such as Camera, Text & Handwriting recognition, and various Apple Intelligence experiences. In this role, you will be tasked with owning project planning and coordination for large Data Engineering initiatives. This includes gathering requirements, scoping efforts, prioritizing tasks, allocating resources, and managing schedules for deliverables. You will represent the Data Engineering team in discussions with Research and Development teams, Data Operations teams, and external vendors, ensuring that data engineering topics are effectively raised, discussed, tracked, and resolved. Your ability to facilitate cross-functional communication will be crucial in ensuring that requirements are well understood and that priorities and delivery schedules are managed effectively. Additionally, you will drive data governance and regulatory/privacy initiatives, ensuring that processes are documented and maintained to meet Apple's high standards. Partnering with the engineering manager, you will help execute long-term engineering initiatives by building a roadmap that balances short-term requests with long-term goals. Your role will also involve identifying problems and opportunities, pitching solutions, and influencing the roadmap of other engineering teams across Apple to enhance the impact and velocity of the Data Engineering team.

Responsibilities

• Own project planning and coordination for large Data Engineering initiatives, including requirements gathering, scoping effort, prioritizing, resource allocation, and schedule of deliverables.
• Represent the DE team in conversations with R&D teams, Data Ops teams, and external vendors to ensure data engineering topics are raised, discussed, tracked, and resolved appropriately.
• Facilitate communication cross-functionally with other teams, ensuring that requirements are well understood, and that priorities and delivery schedules expectations are managed.
• Drive data governance and other regulatory/privacy initiatives and ensure that processes are well documented and maintained to the high standards of Apple.
• Partner with the engineering manager to execute long-term engineering initiatives by building a roadmap that balances short-term requests and long-term initiatives.
• Identify problems/opportunities and pitch solutions (both technical & process oriented) in how Data Engineering can scale its impact and increase velocity.

Requirements

• 5+ years of experience in driving the design and development of data infrastructure and machine learning pipelines as a Technical Program Manager and/or Software Engineer.
• Proven experience in driving the design and development of data tools and infrastructure as a Technical Program Manager and/or as a Software Engineer.
• Familiarity with Machine learning (ML development lifecycle, typical data workflows, and model metrics) and understanding of how data fits into ML.
• Experience working with Python, AWS, Airflow, Spark, Snowflake/Databricks, (No)SQL, Distributed Computing, Dashboards (Tableau, Grafana).
• Experience in understanding and managing Engineering tools & infrastructure and influencing cross-team roadmaps to align with team/project needs.
• High quality program management skills including program structuring and managing multiple work streams interdependently.
• Demonstrated talent for effecting change and driving results through influence, and an ability to navigate complex organizational structures to foster collaboration across functions.

Nice-to-haves

• Understanding of generative technologies (LLMs, diffusion models).
• Proven experience working directly or adjacent to ML data operations (synthetic data creation, human data collection/annotation, data quality management) in support of machine learning features.
• Experience with state-of-the-art ML techniques (transformer architecture, CLIP & other visual and text embedding models etc).

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments
• Relocation assistance
• Participation in Apple's discretionary employee stock programs
• Ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan