AIML - Research Scientist, AI Interpretability & Visualization

Position Overview

We're looking for a Researcher to advance the state of the art in evaluation and development of modern machine learning models with a focus on real-world use of artificial intelligence. A successful candidate will use their expertise to develop interactive systems and strategies that make our AI systems more understandable, transparent, and safe. You need a keen curiosity about rigorous evaluation, a deep understanding of modern machine learning and AI technologies, strong prototyping and development skills, and the ability to communicate sophisticated algorithms clearly. You’ll work with a close-knit team of deeply technical Research Scientists passionate about making machine learning more robust, faster, and easier. Our team often uses data visualizations to help our partners across Apple understand large and complex datasets or evaluate models, and you’ll collaborate with innovative product teams across Apple to deploy projects on 1 billion Apple devices worldwide. We encourage applications from junior to senior-level candidates and strongly suggest you include a cover letter with your application to give us a better sense of your background, expertise, and career goals.

Key Responsibilities

• Define and implement research directions at the forefront of interpretable machine learning.
• Design and implement new tools and visualizations to make designing, building, and deploying machine-learning based products faster and easier.
• Investigate innovative machine learning and artificial intelligence algorithms.
• Contribute to a variety of projects around Apple and translate your ideas into solutions for some of the most ambitious technical challenges in the next generation of Apple products.

Required Qualifications

• PhD or MS in Computer Science, Machine Learning, or a related field, or equivalent experience.
• Proficiency with modern AI technologies and building interactive data visualizations.
• Experience shipping products that use machine learning or tools for machine learning interpretability.
• Substantial contributions to research or practitioner communities, such as publishing papers at top conferences or contributing to open source projects.
• Proven history of turning ideas into actionable tools, guidelines, or products.
• Excellent verbal and written communication and presentation skills.

Preferred Qualifications

• Strong web-development background.