MDS Technical Project Manager

Imagine what you could do here! At Apple, new insights have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just build products — they craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it.

The Manufacturing Design team enables the mass production of Apple's entire product line you can think of. Part of the magic that makes all this possible is a robust set of applications and systems designed and developed by Apple that support a product’s journey from prototype to launch and beyond. As a member of MDS (Manufacturing Design Systems), the system you will work on is a critical part of manufacturing at Apple. Your work will have a significant impact on Apple’s products. This role is responsible for the implementation of software system and solution using within the enclosure manufacturing process and the broader Manufacturing Design organization. Your contribution will ensure that our operational needs are met, boosting greater efficiency, simplicity, cost savings, quality, standardization, and scalability.

Translate Factory Needs to Tech Solutions: Engage deeply with MQE, MDE, GSM, and vendor partners to identify opportunities and requirements into actionable system designs. Define Metrics & Measure Impact: Establish objective success metrics and establish executive-ready monitoring and progress updates. Drive Applied ML & Algorithm Delivery: Lead the planning, execution, and scaling of algorithmic and data deployed onto Apple manufacturing lines. Bridge Science and Engineering: Partner with MLE team to define production requirements—such as inference latency, model retraining cadences, data availability, failover mechanisms, and telemetry. Risk & Lifecycle Management: Proactively identify systemic risks—data quality gaps, edge-case model drift, deployment dependencies, and supplier alignment—before impact on production lines, and work with cross-functional team for mitigation.

BS/MS in Computer Science, Data Science, Industrial Engineering, Operation Research, Statistics, Control Science & Engineering or equivalent with 3+ years of technical program management or engineering delivery experience. Practical experience delivering applied machine learning, operations research (OR), or data-driven optimization systems into real production.

Domain Experience: Experience with constraint programming , heuristic algorithms, or predictive models applied to supply chain, factory scheduling, yield improvement, etc. Operations Acumen: Familiarity with manufacturing processes, tolerance analysis, or quality control methodologies Cross-functional Collaboration: Demonstrated track record of lead and collaborate with diverse technical and operational stakeholders. Agility & Travel: Comfortable navigating ambiguity in dynamic NPI (New Product Introduction) and MP (Mass Production) schedules. Willingness to travel to manufacturing sites as needed.