Engineering Program Manager, Machine Learning and Data - SIML

Engineering Program Manager, Machine Learning and Data - SIML

Would you like to contribute to generative AI and transform how people interact with AI technologies? Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the Data Team of the System Intelligence and Machine Learning (SIML) group within the software engineering organization at Apple. We are responsible for building high-quality ML datasets at scale used to train ML models that power AI-centric features for many Apple products (iPhone, iPad, Mac, Apple Watch, and even AirPods). Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes). AI-centric products are the future of software. At their core, data is the source code of AI, a key component of innovation and inclusive and fair ML products. We invite you to join us at this exciting time. Grow fast and positively impact multiple critical features on your first day at Apple!

Description

Our Data Engineering (DE) team is the critical backbone of our operations, designing and building ML & Data pipelines to support day-to-day operations and automating data flows. The team constantly deals with orchestrating large datasets, some in the scale of petabytes, in addition to making sure we meet regulatory/governance needs and the high data privacy standards of Apple. As the Engineering Program Manager for the Data Engineering group, you will help bring planning and program management excellence for our largest efforts. You will be a champion to scale the team's impact by enabling efficiency, scalability, and streamlined execution. In addition, you will also help accelerate progress on the various tools and technologies used by the team by influencing the roadmap of other engineering teams across Apple.

IN THIS ROLE YOU WILL:

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

Minimum Qualifications

• 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) an 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.

Preferred Qualifications

• 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).

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $165,500 and $248,700, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.