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Principal AI Scientist

Оценка ИИ

Престижная роль в крупной международной компании с возможностью работать над передовыми технологиями (Agentic AI). Отличный пакет бонусов, включая акции (equity) и полную удаленку, делают вакансию очень привлекательной для топ-специалистов.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует исключительной экспертизы в узких областях, таких как Reinforcement Learning и агентные системы, а также наличия публикаций в топовых конференциях. Высокий уровень ответственности за архитектурные решения и менторство команды делает эту позицию крайне сложной.

Анализ зарплаты

Медиана245 000 $
Рынок190 000 $ – 320 000 $
Оценка ИИ

Зарплата для позиции Principal AI Scientist в США в крупных технологических компаниях обычно начинается от $200,000 и может значительно превышать $300,000 с учетом бонусов и акций. Данная роль предполагает высокий уровень компенсации, соответствующий рыночным лидерам.

Сопроводительное письмо

I am writing to express my strong interest in the Principal AI Scientist position at GoDaddy. With a deep background in Reinforcement Learning and autonomous agent design, I am excited by the opportunity to lead research within the Airo Growth and Innovation team. My experience in designing intelligent agents capable of autonomous reasoning and planning aligns perfectly with your mission to simplify the shopping experience for entrepreneurs through state-of-the-art ML.

Throughout my career, I have successfully integrated Large Language Models with RL frameworks to create adaptive, goal-driven behaviors. I have a proven track record of translating complex research into production-ready solutions and mentoring junior scientists. I am particularly drawn to GoDaddy's commitment to empowering everyday entrepreneurs and would welcome the chance to apply my expertise in multi-agent systems and hierarchical RL to drive meaningful business results.

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Описание вакансии

Location Details:

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.

This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands.

Join our Team...

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.

What you'll get to do...

  • 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.

Your experience should include...

  • 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.

You might also have...

  • 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.

We've got your back...We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy’s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way.

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us... GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements.Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com.

Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Python
  • C++
  • Java
  • Scala
  • R
  • Reinforcement Learning
  • Machine Learning
  • Natural Language Processing
  • Deep Learning
  • Hadoop
  • Spark
  • Large Language Models
  • Multi-agent systems
  • Distributed Computing

Возможные вопросы на собеседовании

Позиция сфокусирована на агентном ИИ, поэтому важно понимать опыт кандидата в создании автономных систем.

Расскажите о наиболее сложной архитектуре агентного ИИ, которую вы разработали: как вы реализовали механизмы планирования и использования инструментов?

RL является ключевым требованием; необходимо оценить глубину теоретических и практических знаний.

С какими основными трудностями вы сталкивались при масштабировании алгоритмов Reinforcement Learning в продакшн-среде и как вы их решали?

Вакансия упоминает интеграцию LLM и RL для создания адаптивного поведения.

Как вы подходите к проблеме согласования (alignment) и формирования вознаграждений при интеграции больших языковых моделей с фреймворками обучения с подкреплением?

Роль Principal подразумевает лидерство и развитие команды.

Опишите ваш опыт менторства: как вы помогали младшим специалистам расти в области ML-исследований?

GoDaddy — это бизнес-ориентированная компания, важно уметь превращать теорию в продукт.

Как вы балансируете между проведением долгосрочных фундаментальных исследований и необходимостью поставки конкретных бизнес-результатов в сжатые сроки?

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