Ebay Senior Researcher - Responsible AI 

Cuba, Havana 

742629432

For this role you will apply your background in rigorous evaluation methods in machine learning. Research areas of particular interest for this team include, but are not limited to

• You will lead the application of end-to-end evaluation methods to understand how AI systems can be designed with equity, fairness, safety, and robustness as first-class concerns alongside business performance.
• Collaborate with applied researchers and applied engineering teams to drive multiple research projects.
• Formulate problems, gather data, generate hypotheses, develop and conduct model and algorithm evaluations, conduct studies and experiments, synthesize results, and enable tooling to deliver safe, ethical business applications.
• Act as a subject matter expert and inspiring leader in responsible AI, internally for the company and at industry conferences, and contribute to publications and thought leadership content.

• PhD in Computer Science, Artificial Intelligence, Informatics, or related fields
• Deep understanding of responsible AI topics such as evaluation techniques for machine learning models and statistical approaches to evaluation and their relationship with legal, philosophical and socio-technical concerns.
• Research publications in prominent venues such as conference or journals, especially in the area of responsible AI.
• Expertise in socio-technical aspects of AI (e.g., equity and fairness, ethics, safety, robustness, in the context of AI/ML).
• Comfort with rapid and disciplined software development processes.
• Practical research experience and/or software engineering in collaborative, dynamic project settings.

• Master's degree or PhD with relevant work experience in Computer Science, Artificial Intelligence, Statistics, Engineering, Informatics, or related fields with several years of experience in an industry research and development setting.
• Proficient understanding of fundamental AI and ML evaluation techniques.
• Practical experience with ML development pipelines and tooling.
• Proven expertise in many of these areas or interest in generalizing your contributions to a variety of modalities and model architectures.