About the job
Location Details:
At GoDaddy, our vision of the future of work varies by team. While some teams are fully office-based, others enjoy a hybrid setup, working remotely on selected days and in the office on others. Some teams operate entirely remotely.
This particular role is classified as a hybrid position. You will split your time between remote work from home and in-office collaboration, so proximity to the office is essential. The frequency of in-office work may range from several times a week to just once a month or quarter, as determined by team leadership. The hiring manager will provide more details about the hybrid work structure for this team.
Please note, this position is not available for candidates residing in Alaska, Mississippi, North Dakota, or the Virgin Islands.
Join Our Innovative Team...
As part of the Airo Growth and Innovation division at GoDaddy, we are on the lookout for a Principal AI/Machine Learning Scientist to join our core Applied ML team. Our mission is to cultivate and expand a community of ML scientists and engineers dedicated to learning, sharing, and growing together. We are focused on deeply understanding all major business units and strive to empower business outcomes through the use of AI and cutting-edge ML algorithms.
This core Applied AI and Machine Learning team leverages large-scale data to enhance various business functions. Our objective is to develop a seamless navigation experience across different channels and web pages, simplifying the shopping journey for entrepreneurs worldwide and allowing them to efficiently find what they need on our platform.
We are seeking a seasoned AI/ML Scientist to spearhead research and development in Agentic AI systems and Reinforcement Learning (RL). This role will focus on crafting intelligent agents that are capable of autonomous decision-making, planning, and reasoning within complex settings. You will operate at the crossroads of large-scale foundational models, multi-agent systems, and RL-based optimization, driving innovation for next-generation AI products.
Key Responsibilities:
- Lead the research and development of advanced Reinforcement Learning algorithms, including policy optimization, hierarchical RL, and multi-agent RL systems.
- Design and implement agentic architectures to facilitate autonomous reasoning, planning, and sophisticated tool utilization.
- Pioneer the integration of Large Language Models with RL to create transformative AI solutions.
