Principal AI Scientist

GoDaddy•Seattle, WA

7d•Hybrid

About The Position

Our team is a part of the Airo Growth and Innovation within GoDaddy, and we are looking to have a principal AI / machine learning scientist join this core Applied ML team. Our goal is to build and grow a community of ML scientists and engineers to learn, share and grow. We are committed to understanding all major business units very closely and we thrive to empower business results by leveraging AI and state-of-the-art ML algorithms. This core Applied AI and Machine Learning team utilizes large-scale data to power various business areas, and our goal is to create cohesive navigation experience across channels and web pages, to help simplify and enhance the shopping experience for everyday entrepreneurs across the world to quickly find what they need on our website. We are seeking a highly experienced AI/ML Scientist to lead research and development in Agentic AI systems and Reinforcement Learning (RL). This role focuses on designing intelligent agents capable of autonomous decision-making, planning, and reasoning in complex environments. You will work at the intersection of large-scale foundation models, multi-agent systems, and RL-based optimization, driving innovation for next-generation AI products.

Requirements

Strong background in both machine learning/NLP and software development with hands-on Deep Neural Network experience.
Proven expertise in Reinforcement Learning algorithms and autonomous agent design.
Advanced algorithm design and programming skills in low-level languages (C++/Java) and scripting languages (Python/R/Scala).
Experience working with live data including data cleaning, visualization, and modeling.
Experience with distributed computing frameworks (Hadoop/Spark).
Track record of solving meaningful real-world problems using principled ML techniques.

Nice To Haves

PhD (Preferred) in Machine Learning, Artificial Intelligence, or related field with focus on Reinforcement Learning.
Publications in top-tier AI/ML conferences (NeurIPS, ICML, ICLR, AAAI, ACL, etc.).
Experience with multi-agent systems and game-theoretic approaches.
Background in integrating foundation models with traditional RL frameworks.
Contributions to open-source AI/ML projects or frameworks.
Experience deploying ML models at scale in production environments.
Track record of mentoring and developing technical talent.

Responsibilities

Lead research and development of advanced Reinforcement Learning algorithms including policy optimization, hierarchical RL, and multi-agent RL systems.
Design and implement agentic architectures that enable autonomous reasoning, planning, and sophisticated tool use.
Pioneer the integration of Large Language Models with RL to create adaptive, goal-driven AI behaviors.
Formulate hypotheses and conduct large-scale experiments to continuously improve agent performance and capabilities.
Build sophisticated simulation environments for testing agentic behaviors and reward strategies.
Leverage large-scale data to create cohesive navigation experiences that simplify shopping for entrepreneurs worldwide.
Partner with product and engineering teams to translate breakthrough research into production-ready AI solutions.
Mentor and develop junior scientists and engineers on RL and agentic AI best practices.
Drive innovation across major business units by applying state-of-the-art ML algorithms to real-world challenges.