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Apple AIML - ML Engineer, Safety & Red Teaming in Pittsburgh, Pennsylvania

AIML - ML Engineer, Safety & Red Teaming

Pittsburgh,Pennsylvania,United States

Machine Learning and AI

Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for 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 generative AI. As a member of the Apple HCMI group, you will be working on Apple's generative models that will power a wide array of new features. Our team is currently working on large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.

Description

  • Develop models, tools, metrics, and datasets for assessing and evaluating the safety of generative models over the model deployment lifecycle - Develop models, models, and tools to interpret and explain failures in language and diffusion models - Build and maintain human annotation and red teaming pipelines to assess quality and risk of various Apple products - Prototype, implement, and evaluate new ML models and algorithms for red teaming LLMs

Minimum Qualifications

  • Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages

  • Background in generative models, natural language processing, LLMs, or diffusion models

  • Experience with failure analysis, quality engineering, or robustness analysis for AI/ML based features

  • Experience working with crowd-based annotations and human evaluations

  • Experience working on explainability and interpretation of AI/ML models

  • Work with highly-sensitive content with exposure to offensive and controversial content

Key Qualifications

Preferred Qualifications

  • BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues

  • Proven track record of contributing to diverse teams in a collaborative environment

Education & Experience

Additional Requirements

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)

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Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (Opens in a new window) .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area.

Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .

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