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 ISE, SIML - Robustness Analysis Manager - Cupertino, California, United States

Job information
Posted by: Apple 
Hiring entity type: Retail 
Work authorization: Not Specified for United States
Position type: Direct Hire, Full-Time 
Compensation: ******
Benefits: See below
Relocation: Not specified 
Position functions: Management - General
Travel: Unspecified 
Accept candidates: from anywhere 
Languages: English - Fluent
Minimum education: See below 
Minimum years experience: See below 
Resumes accepted in: English
Cover letter: No cover letter requested
Job code: 200289270 / Latpro-3825541 
Date posted: Dec-01-2021
State, Zip: California, 95014


ISE, SIML - Robustness Analysis Manager

Santa Clara Valley (Cupertino) , California , United States

Machine Learning and AI


Posted: Sep 20, 2021

Weekly Hours: 40

Role Number: 200289270

The promotion of inclusion and fairness is a priority for Apple. It applies to our products and features, including those which are powered by machine learning models. The System Intelligence and Machine Learning (SIML) group is responsible for crafting machine learning solutions which transform the way millions of people capture, discover and share the most special moments of their lives, on all Apple platforms (macOS, iOS, tvOS, watchOS). Examples include face detection, scene classification, OCR, handwriting recognition... The group combines research and development in a dynamic and engaging environment. Within SIML, we assess the robustness of features powered by ML, in addition to designing and building high quality datasets at scale. At the heart of machine learning, data defines how Apple features and products operate and what is the final user experience that will impact millions of our customers! This is an exciting time to join us: grow fast, and have a positive impact on multiple key features on your first day at Apple!

Key Qualifications

  • - 2+ years of experience as a software manager
  • Passion to create great products which perform equally well for diverse categories of customers, within Apple's global user base
  • Strong experience in quantitative methods, data analysis and machine learning, leading to a deep understanding of the challenges associated to building ML datasets and machine learning models (potential biases, potential failure modes)
  • Excellent communication, collaboration and planning skills
  • Capacity to operate at the intersection of ethics, product experience and data science: translate product needs (e.g. fairness) into analytical requirements; design and lead experiments to answer feature level questions
  • Capacity to build a team and establish innovative and agile processes in order to achieve a high level of service and for scalability
  • Creative approach when facing situations of trade-offs/decision under uncertainty
  • Strong programming skills in Python


Our data team historically focused on data acquisition, data science, and data annotation. Each year, we power dozens of features and work closely with ML teams across the entire company. Apple's commitment to deliver incredible experiences to a global and diverse set of users, in full respect of their privacy, has recently led to the development of a new function, Robustness Analysis (RA). RA IS A DATA DRIVEN INITIATIVE TO: - monitor model performance on relevant axes - surface, measure and mitigate ML failure modes, in order to improve overall user experience and reduce risks, with specific attention given to inclusion and fairness This position focuses on managing and growing a team dedicated to this novel function. This requires to: - Formalize charter and modalities for collaboration across teams, to maximize the impact of RA - Incubate RA processes through the full support of key ML features: identification of relevant metrics and audit axes for each feature considered (through product intuition and data science), identification and prioritization of failure modes, reporting of metrics, drive of mitigation plans - With the support of infrastructure teams, design the specs and drive the implementation of a testing and reporting infrastructure and of visualization tools adapted to robustness analysis - Multiply sources of user inputs to help surface potential issues and define priority and target experience, with privacy and scalability in mind (eg on-device statistics, feedback from internal population, assessment of downstream impact...) - Plan conditions of scalability of robustness analysis within the software organization. In particular, design tools and processes to be scalable and reusable, whenever possible, and promote principles of robustness within SIML and beyond (eg influence data collection/annotation processes) - Become key contact within our organization, in company wide efforts related to fairness and inclusion, robustness analysis, interpretability

Education & Experience

Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, Econometrics, Operations Research, Social Sciences, Statistics, or equivalent professional experience


See job description


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