AIML - ML Data Scientist, Safety & Red Teaming
Job Description
Summary
Would you like to play a part in building the next generation of generative AI applications at Apple? We’re looking for data scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
In this role, you’ll have the opportunity to tackle innovative problems in machine learning, particularly focused on LLM\'s. As a member of the Apple HCMI/Responsible AI group, you will be working on Apple\'s generative models that will power a wide array of new features, as well as longer term research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
In this role, you’ll have the opportunity to tackle innovative problems in machine learning, particularly focused on LLM\'s. As a member of the Apple HCMI/Responsible AI group, you will be working on Apple\'s generative models that will power a wide array of new features, as well as longer term research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
Description
- Research and develop Responsible AI evaluation methods to improve the quality of Apple Intelligence\'s user facing products
- Create evaluation data sets to solve difficult, non-routine analysis problems; applying sophisticated analytical methods as needed
- Conduct analyses that includes data gathering and requirements specification, processing, analysis, ongoing work, and presentations
- Build and prototype analysis pipelines iteratively to provide insights at large-scale
- Develop extensive knowledge of data structures and metrics, advocating for changes where needed for product development
- Partner closely with engineering teams on core machine learning algorithms and systems that are part of how features work
- Create evaluation data sets to solve difficult, non-routine analysis problems; applying sophisticated analytical methods as needed
- Conduct analyses that includes data gathering and requirements specification, processing, analysis, ongoing work, and presentations
- Build and prototype analysis pipelines iteratively to provide insights at large-scale
- Develop extensive knowledge of data structures and metrics, advocating for changes where needed for product development
- Partner closely with engineering teams on core machine learning algorithms and systems that are part of how features work
Minimum Qualifications
- Strong programming skills: Including data-querying skills (SQL and/or Spark, etc.) and experience with a scripting language for data processing and development (e.g., Python, R, or Scala)
- Proficiency in data science, machine learning, and analytics: Including statistical data analysis and A/B testing. Experience crafting, conducting, analyzing, and interpreting experiments and investigations
- Experience articulating and answering business questions by applying statistical techniques to available data sources
- Experience collecting and analyzing crowd-sourced data, language data, image data, and/or multi-modal data
- Strong interpersonal skills: Proven ability to explain difficult technical topics (esp. causal topics) to everyone from data scientists to engineers to business partners
- Work with highly-sensitive content with exposure to offensive and controversial content
Preferred Qualifications
- Experience working in the Responsible AI space
- Experience dealing with highly multi-labeled, nuanced, and often conflicting data sources
- Ability to thrive in fast-paced environment, deal with uncertainty, and adapt to new and changing requirements
- History driving projects of varying sizes and scopes - some will take months and some weeks — and you will need to cut through ambiguity and know when to dive deep
- Advanced degree or equivalent experience in a quantitative field such as Statistics, Operations Research, Bioinformatics, Cognitive Science, Economics, Linguistics, Psychology, Computer Science, Sociology, Mathematics, Physics, or similar field
- Proven track record of contributing to diverse teams in a collaborative environment
- A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills
Pay & Benefits
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