Software Test Engineer, Sensing & Connectivity

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 Fitness Journal - among many more. As a member of our dynamic group you will have the rare and rewarding opportunity to craft upcoming products that will delight and inspire our customers. Additionally you will have the opportunity to work on 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 an engineer with a fundamental understanding of ML the ability to validate these models and the supporting software pieces. If this is you we would be delighted to hear from you.

The Sensing and Connectivity QE team is looking for a Software Development Engineer in Test to validate the algorithms and AI models behind our location context features. We work in a fast-paced environment that depends on a tight relationship between test and development.

In this role you will:nnOwn the quality of the end-to-end experiences powered by location context and define the quality assurance strategy for our ML models including validation of training data features and the design and implementation of the algorithms and back your conclusions with sound automated tests that qualify features and measure performance and system memory usage along with automated monitoring and quality metrics that continuously track feature the KPIs that define the projects success build the dashboards behind them and track progress across synthetic data at scale to validate on-device models across a large number of highly variable environments applying the reasoning analytics and data-science judgment and GenAI where it accelerates the work needed to achieve meaningful variation and data-collection and replay infrastructure that scales across diverse real-world scenarios while adhering to Apples privacy process and evaluate large structured and unstructured in and present at user study reviews code reviews and data with upstream (e.g. hardware) and downstream (e.g. app) stakeholders to drive the end-to-end user experience of the feature.

BS MS or PhD in Computer Science / Electrical Engineering / Mechanical Engineering or in validating AI models crafting benchmarks and evaluation protocols and performing statistical in designing AI-assisted workflows using GenAI to automate and accelerate testing debugging and metrics at coding in Python and/or at data analysis data visualization and reporting.n

Familiarity with building data-collection and replay tooling and evaluation pipelines for large-scale data working with databases (SQL/NoSQL) comfortable with query languages and designing tables views and testing hardware and/or testing software (including designing implementing and executing test plans) is a -oriented able to find bugs investigate and debug issues and drive solutions to difficult analytical and problem-solving skills self-motivated persistent and about location technologies and fitness.n