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🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Apple • Cupertino, California, United States
Role & seniority: Engineer (ML quality assurance for location context features); seniority not specified
Stack/tools: ML model validation and integration; automated testing; Python and/or MATLAB; data analysis & visualization; data pipelines; dashboards; SQL/NoSQL databases
Define QA strategies for ML models, including validation of training data, features, and labels; own end-to-end feature quality for location context features
Develop automated tests to qualify features, measure performance and memory usage, and track progress across releases
Identify KPIs, build dashboards, and monitor project success and quality across releases
BS, MS, or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, or equivalent
Background in time-series analysis, signal processing, sensor fusion, AI models, or statistics
Proficiency in Python and/or MATLAB; data analysis, visualization, and reporting
Experience building data pipelines for large-scale data processing; familiarity with databases (SQL/NoSQL)
Experience validating AI models, crafting benchmarks/evaluation protocols, and statistical analysis
Comfort with query languages and designing tables, views, indices
Familiarity testing hardware/software (designing/executing test plans)
Detail-oriented, strong bug-finding and debugging skills; strong analytical/problem-solving abilities
Interest in location
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
DESCRIPTION
Define quality assurance strategies for ML models, including validation of training data, features, and labels. In this position, you will be responsible for owning the quality of the end-to-end features powered by location context features. Develop automated tests that qualify the features, measure performance, and system memory usage. Identify KPIs that define the project’s success, dashboard, and track progress across releases.
MINIMUM QUALIFICATIONS
BS, MS, or PhD in Computer Science / Electrical Engineering / Mechanical
PREFERRED QUALIFICATIONS
Experience in validating AI models, crafting benchmarks and evaluation protocols, and performing statistical analysis Experience working with databases (SQL/NoSQL), comfortable with query languages and designing tables, views, indices Familiarity testing hardware and/or testing software (including designing, implementing, and executing test plans) is a plus Detail-oriented, able to find bugs, investigate & debug issues, and drive solutions to difficult problems Excellent analytical and problem-solving skills, self-motivated, laser-focused, and solution-oriented Passionate about location technologies and fitness