Currently pursuing aPhD/ Master’s degree in Computer Science, Engineering, Data Science, Mathematics, or related field.
Must have at least three additional semesters of school remaining (graduation date 2027 or later)
Solid background in machine learning, deep learning, language models and optimization.
Preferred Qualifications
Currently pursuing a PhD inComputer Science, Engineering, Data Science, Mathematics, or related field.
Proficiency in Python and experience with PyTorch, TensorFlow and ONNX.
Research or hands-on experience in efficient model architecture and model compression techniques (quantization, pruning, distillation, etc.).
Research or hands-on experience with language models (e.g., BERT, LLaMA, GPT).
Publications in top-tier relevant ML venues (e.g., NeurIPS, ICML, ACL, or ICLR).
Previous industry experience as a Data Scientist / Intern.
Solid background in machine learning, deep learning, language models and optimization.
Strong analytical thinking and independent research capabilities.
Excellent communication, collaboration, and writing skills.
Responsibilities
Design, implement, and evaluate methods to enable efficient, secure and optimized deployment of AI models on edge or resource-constrained platforms.
Drive innovation and practical research, iteratively improving solutions based on empirical results, working with large-scale textual datasets.
Document research findings and contribute to publications, open-source projects, or patent filings as appropriate.
Formulate approaches to solve problems using well defined algorithms and data sources
Incorporate an understanding of product functionality and customer perspective to provide context for those problems.
Engage with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers.