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 Robustness Analysis, ML Engineer - 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: Computers - Programming Languages
Computers - Other
Computers - Platforms
Computers - Networks
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: 200296204 / Latpro-3831523 
Date posted: Oct-24-2021
State, Zip: California, 95014


Robustness Analysis, ML Engineer

Santa Clara Valley (Cupertino) , California , United States

Machine Learning and AI


Posted: Oct 5, 2021

Weekly Hours: 40

Role Number: 200296204

Do you think computer vision and machine learning can change the world? Do you think it can transform the way millions of people capture, discover and share the most special moments of their lives? We truly believe it can! Our data team is responsible for crafting 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 an impact on multiple key features to deliver robust solutions to keep children safe.

Key Qualifications

  • You have experience in training machine learning models (preferably computer vision and text)
  • You're aware of the challenges associated to building ML datasets and machine learning models (eg face detector): definition and coverage of target data distribution, potential biases, potential failure modes (eg low light, pale/dark skin etc...)
  • You have strong Python coding skills which enable you to manipulate data at scale & to run ML models
  • You have creativity and a good sense of product, which enable you to build tools/frameworks that are impactful and convenient to use by different types of end-users
  • You're ambitious, pragmatic and result focused
  • You show strong communication skills and proactivity
  • You are passionate about building technology to help keep children safe


Our team focuses on data collection/generation, smart filtering/selection, annotation, as well as robustness analysis (RA). Each year, we power dozens of features and work closely with ML teams across the entire company. Apple's commitment to delivering incredible experiences to a global and diverse set of users in full respect of their privacy leads our team to explore innovative data collection processes. The position focuses on contributing to structure a FA function across SWE, by leading FA operations for key Apple features. This includes: - Define product-centered axes of analysis (eg lighting conditions for images) and associated classes (eg low light < 100 ISO, backlit, ...) relevant to target feature, in collaboration with model DRI and feature DRI - Identify other potential failure modes based on a data-driven approach - When applicable, benchmark model using targeted public datasets - Characterize potential biases in training set along chosen axes - Request data collection efforts and/or implement smart pipelines based on advanced ML technology and humans in the loop to create test sets covering the various axes of investigation - Participate in the design of a robustness analysis framework that continuously tests successive versions of target model. The infrastructure includes a testing framework, reporting tools & data visualization, with a web front-end. - Report progress and issues found in technical meetings and sponsor meetings - Suggest mitigation options (data and/or model) and lead mitigation experiments, when issues are found - In this position, you will interact with product teams and with R&D DRIs. - Ability to handle sensitive and challenging datasets

Education & Experience

M.S. or PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning or comparable professional experience

Additional Requirements

  • Previous experience working in the domain of child safety is a plus


See job description


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