Conduct research in areas such as training data, pre-training, and model training.
Research and prototype innovative evaluation methods.
Collaborate with product and infrastructure teams to build and scale tools for responsible deployment.
Design and develop models that drive real-world impact and continuous improvement.
Qualifications
Proven track record of generating new ideas or enhancing existing ones in machine learning, evidenced by first-author publications or notable projects.
Ability to lead and execute a research agenda, selecting impactful problems and managing long-term projects independently.
Experience in developing novel techniques for measuring and mitigating ML model performance.
Comfortable working across research and product teams in a cross-functional environment.