Human Centered AI - Data Scientist - ASE
Imagine what you could do here. At Apple, great new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish!
Are you passionate about music, movies, and the world of Artificial Intelligence and Machine Learning? So are we! Join our Human-Centered AI team for Apple Products. In this role, you'll represent the user perspective on new features, review and analyze data, and evaluate AI models powering everything from search and recommendations to other innovative features. Collaborate with Data Scientists, Researchers, and Engineers to drive improvements across our platforms.
Our team is comprised of very talented individuals who are passionate about LLM and ensuring Apple services are at their best. As part of the Human-Centered AI team, you'll play a central role in enhancing the user experience.
Responsibilities include:
- Collaborate with Engineering, Products, Research, Operations, and Editorial teams to evaluate algorithms and AI models powering various features, identifying opportunities for improvement.
- Build data products (feature datasets, analyses, models, etc.) and scalable tools (typically in Python or Scala) to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management.
- Create structured evaluations to assess the quality of AI-generated responses, ensuring they align with company standards and customer expectations.
- Create evaluation task design and guidelines; identify a relevant data annotation platform to run evaluations at scale.
- Implement metrics to measure the effectiveness and accuracy of models to ensure they meet performance standards.
- Establish data quality thresholds and reporting on metrics & insights to inform feature business decisions.
- Monitor LLM performance in production environments through human evaluations, identifying trends, and raising alerts when quality degradation occurs.
- Perform detailed failure analysis to understand model weaknesses and identify areas for improvement, offering actionable insights to engineers
- Maintain high standards for data quality and continuously enhance processes based on both quantitative and qualitative feedback
- Experience with machine learning concepts, including model evaluation metrics, and data analysis. Proven data analysis expertise using SQL, Python, and Tableau to deliver actionable insights
- Experience with Large Language Models and evaluation techniques
- Fluency in English reading, writing and comprehension skills to partner with international teams
- Fluent in another language then English (reading, writing, and comprehension skills) to support the language specific market
- Expert linguistic and cultural skills for a non English market to accurately represent user experience in early development cycles
- Ability to analyze complex issues, and identify potential problems with LLM outputs to improve quality with keen attention to detail
- Effective collaboration with cross-functional teams to define ML/LLM evaluation requirements
- Experience crafting, conducting, analyzing, and interpreting experiments and investigations
- Excellent communication skills
- Flexibility to work early morning or late night shift patterns required