Health Algorithms Validation & Verification Engineer
Apple
Health Algorithms Validation & Verification Engineer
Job Description
The Applied Sensing & Health team has built innovative ways for users to improve their health, watch for their lives, and get personalized insights from their 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 spanning health, fitness, and safety. This has enabled us to deliver meaningful features like Cardio Fitness, Journaling Suggestions, Fall and Crash Detection, and our latest advances to bring our suite of Fitness metrics to AirPods Pro 3, delivering 50 workout types in a single year. We are a dynamic, collaborative group that works at the intersection of scientific research and product development. We develop science-backed designs of best-in-class AI/ML models that capture the multifactorial nature of human health and behavior, delivering insights straight to our customers. We promote innovation and new technology to further improve our creative output. We are seeking a tenacious and passionate person to join this amazing team. If you feel this is you, we'd love to hear from you. In this role, you will be highly involved in driving design data quality and algorithm performance to develop our next generation of Health and Fitness features. This includes evaluating large user study datasets, design reviews, algorithm testing, bug reporting and triaging.
Locations
- San Diego, California, United States 92128
Salary
Salary not disclosed
Skills Required
- machine learningintermediate
- integration of foundation modelsintermediate
- adaptation of foundation modelsintermediate
- tuning of foundation modelsintermediate
- contextual sensingintermediate
- innovative study designintermediate
- evaluating large user study datasetsintermediate
- design reviewsintermediate
- algorithm testingintermediate
- bug reportingintermediate
- bug triagingintermediate
- driving design data qualityintermediate
- algorithm performanceintermediate
Required Qualifications
- BS, MS, or PhD in Computer Science / Electrical Engineering / Mechanical Engineering or equivalent (degree in phd in computer science)
- Background in one or more of the following domains: time-series analysis, signal processing, sensor fusion, AI models, statistics, health & fitness, (experience)
- Proficient at coding in Python and/or Matlab (experience)
- Proficient at data analysis, data visualization, and reporting (experience)
- Experience in validating AI models, crafting benchmarks and evaluation protocols, and performing statistical analysis. (experience)
Preferred Qualifications
- Familiarity building data pipelines for large-scale data processing (experience)
- Experience working with databases (SQL/NoSQL), comfortable with query languages and designing tables, views, indices, familiarity with AWS services/API such as S3 is a plus (experience)
- Familiarity testing hardware and/or testing software (including designing, implementing and executing test plans) is a plus (experience)
- Detail-oriented, able to find bugs, investigate & debug issues, and drive solutions to difficult problems (experience)
- Excellent analytical and problem solving skills, self-motivated, laser-focused, and solution-oriented (experience)
Responsibilities
- In this role, you will be highly involved in driving design data quality and algorithm performance to develop our next generation of Health and Fitness features. This includes evaluating large user study datasets, design reviews, algorithm testing, bug reporting and triaging.
- Challenge the design and implementation of the algorithm
- Design and perform analytics for algorithm verification and validation
- Create automated monitoring and quality assurance metrics to constantly track feature performance
- Profile, process, and evaluate large structured and unstructured datasets
- Participate and present in user study review, code review, and data review
- Perform comprehensive assessments of AI model outputs to identify areas of enhancement and facilitate algorithm improvements
- Communicate with upstream (e.g. hardware) and downstream (e.g. app) stakeholders to drive end-to-end user experience of the feature.
Tags & Categories
Health Algorithms Validation & Verification Engineer
Apple
Health Algorithms Validation & Verification Engineer
Job Description
The Applied Sensing & Health team has built innovative ways for users to improve their health, watch for their lives, and get personalized insights from their 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 spanning health, fitness, and safety. This has enabled us to deliver meaningful features like Cardio Fitness, Journaling Suggestions, Fall and Crash Detection, and our latest advances to bring our suite of Fitness metrics to AirPods Pro 3, delivering 50 workout types in a single year. We are a dynamic, collaborative group that works at the intersection of scientific research and product development. We develop science-backed designs of best-in-class AI/ML models that capture the multifactorial nature of human health and behavior, delivering insights straight to our customers. We promote innovation and new technology to further improve our creative output. We are seeking a tenacious and passionate person to join this amazing team. If you feel this is you, we'd love to hear from you. In this role, you will be highly involved in driving design data quality and algorithm performance to develop our next generation of Health and Fitness features. This includes evaluating large user study datasets, design reviews, algorithm testing, bug reporting and triaging.
Locations
- San Diego, California, United States 92128
Salary
Salary not disclosed
Skills Required
- machine learningintermediate
- integration of foundation modelsintermediate
- adaptation of foundation modelsintermediate
- tuning of foundation modelsintermediate
- contextual sensingintermediate
- innovative study designintermediate
- evaluating large user study datasetsintermediate
- design reviewsintermediate
- algorithm testingintermediate
- bug reportingintermediate
- bug triagingintermediate
- driving design data qualityintermediate
- algorithm performanceintermediate
Required Qualifications
- BS, MS, or PhD in Computer Science / Electrical Engineering / Mechanical Engineering or equivalent (degree in phd in computer science)
- Background in one or more of the following domains: time-series analysis, signal processing, sensor fusion, AI models, statistics, health & fitness, (experience)
- Proficient at coding in Python and/or Matlab (experience)
- Proficient at data analysis, data visualization, and reporting (experience)
- Experience in validating AI models, crafting benchmarks and evaluation protocols, and performing statistical analysis. (experience)
Preferred Qualifications
- Familiarity building data pipelines for large-scale data processing (experience)
- Experience working with databases (SQL/NoSQL), comfortable with query languages and designing tables, views, indices, familiarity with AWS services/API such as S3 is a plus (experience)
- Familiarity testing hardware and/or testing software (including designing, implementing and executing test plans) is a plus (experience)
- Detail-oriented, able to find bugs, investigate & debug issues, and drive solutions to difficult problems (experience)
- Excellent analytical and problem solving skills, self-motivated, laser-focused, and solution-oriented (experience)
Responsibilities
- In this role, you will be highly involved in driving design data quality and algorithm performance to develop our next generation of Health and Fitness features. This includes evaluating large user study datasets, design reviews, algorithm testing, bug reporting and triaging.
- Challenge the design and implementation of the algorithm
- Design and perform analytics for algorithm verification and validation
- Create automated monitoring and quality assurance metrics to constantly track feature performance
- Profile, process, and evaluate large structured and unstructured datasets
- Participate and present in user study review, code review, and data review
- Perform comprehensive assessments of AI model outputs to identify areas of enhancement and facilitate algorithm improvements
- Communicate with upstream (e.g. hardware) and downstream (e.g. app) stakeholders to drive end-to-end user experience of the feature.
Tags & Categories