Description

This role involves collaboration with teams at Apple focused on developing foundation models, including ML engineers, data scientists, and ML infrastructure engineers. Your primary responsibilities will include developing methods for the evaluation and enhancement of foundation models, conduct thorough failure analysis on large multimodal models, develop tools for analyzing and visualizing data, design and implement experiment (DOE) for engineering studies and large scale user studies as well as contribute in defining feature specifications and anticipated user experience based on data insights.

Minimum Qualifications

BS and a minimum of 3 years relevant industry experience
3+ years of experience with significant experience in large-scale data analytic
Solid foundation in data science, deep learning and statistics
Demonstrated experience in in-depth analysis of machine learning model failures
Familiarity with various foundation models, such as SAM, LLAMA, LLaVA, CGPT4V, CLIP
Proficiency in Python

Preferred Qualifications

5+ years of experience with significant experience in large-scale data analytics
Deep expertise in data and model evaluation
Proficiency in Data Centric AI
Experience with analytical tools such as Jupyter, Pandas, NumPy, Matplotlib
Experience in training models using frameworks like PyTorch, TensorFlow, Jax, etc
Good verbal and written communication skills