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Apple Inc. is seeking a Manager to lead the Sensing and Connectivity - Location Context team in Cupertino. You will guide a group of engineers evaluating ML models for location context features and own the quality engineering, test automation, and CI across releases.
You will set evaluation strategy, define KPIs, dashboards, collaborate with hardware and software partners, and mentor the team to deliver reliable, privacy-conscious AI features for Maps, Fitness, and other apps.
Join the Sensing and Connectivity - Location Context team that powers critical experiences in Apple products. Our team works on providing personalized insights from users' daily patterns through multimodal sensing and AI models. This team combines advanced machine learning, including integration, adaptation, and tuning of foundation models, with contextual sensing, bolstered by innovative study design, to derive user insights for Maps and Fitness applications, Journal — among many more.As the leader of this team, you will have the rare and rewarding opportunity to shape upcoming products that will delight and inspire our customers. You and your team will own the quality of cutting edge location intelligence features powered by ML models across various operating systems, including iOS and watchOS. We develop science-backed designs of AI/ML models that capture the complex interplay of human health and behavior, providing valuable insights directly to our customers. We foster innovation and embrace new technology to enhance our creative capabilities. We are seeking a manager who pairs a working understanding of ML with a track record of building and growing teams that validate these models and the supporting software.If this is you, we would be delighted to hear from you.
The Sensing and Connectivity team is looking for a manager to lead a talented group of engineers who evaluate the algorithms and AI models behind our location context features, and who also own the quality engineering that ships them: test automation, software testing, and continuous integration. We work in a fast-paced environment that depends on a tight relationship between evaluation and development. You'll evaluate probabilistic, on-device models, defining what *correct* means where ground truth is scarce and real-world behavior can't be fully simulated. In this role you will: