Applied Researcher II

What you'll do

• Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
• Conduct high-impact applied research to integrate the latest AI developments into next-generation customer experiences.
• Leverage technologies like Pytorch, AWS Ultraclusters, and VectorDBs to extract insights from large numeric and textual datasets.
• Deliver AI-powered products by partnering with cross-functional teams of data scientists, software engineers, and product managers.
• Translate complex technical work into tangible business goals for stakeholders.
• Own and pursue a research agenda by identifying impactful problems and autonomously carrying out long-running projects.
• Deliver libraries, platform-level code, or solution-level code to existing products.

What we're looking for

• Currently pursuing or holds a PhD in a relevant field with 2 years of applied research experience.
• Holds an M.S. in a relevant field with 4 years of applied research experience.
• Has hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• Possesses a deep understanding of the foundations of AI methodologies.
• Experience building large deep learning models for language, images, events, or graphs.
• Expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
• Track record of delivering models at scale in terms of training data and inference volumes.
• Experience delivering libraries, platform-level code, or solution-level code to existing products.
• Track record of new ideas or improvements in machine learning, such as first-author publications (preferred).
• PhD in Computer Science, Machine Learning, or related fields (preferred).
• Multiple publications on pre-training large language models or deep learning theory (preferred).
• Experience training a large language model from scratch or scaling graph models to over 50m nodes (preferred).
• Experience optimizing training for a 10B+ model or experience with compiler design (preferred).
• PhD focus on adversarial machine learning, red teaming, or model alignment (preferred).