- Страна
- США
- Зарплата
- 45 $ – 75 $
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Earth Science Tutor
Престижная компания с амбициозной миссией и конкурентной почасовой оплатой. Гибкий формат работы (удаленно) и возможность напрямую влиять на развитие передовых технологий делают вакансию крайне привлекательной для ученых.
Сложность вакансии
Высокая сложность обусловлена требованием ученой степени (магистр или PhD) и глубокой специализации в узких областях наук о Земле. Работа требует не только научных знаний, но и навыков технического письма, а также готовности работать в быстро меняющейся среде ИИ-стартапа.
Анализ зарплаты
Предлагаемая ставка ($45-$75 в час) соответствует или даже несколько превышает рыночные показатели для специалистов с PhD, работающих в сфере разметки данных и обучения ИИ. В пересчете на полную занятость это составляет около $93,000 - $156,000 в год, что сопоставимо с зарплатами научных сотрудников в США.
Сопроводительное письмо
I am writing to express my strong interest in the Earth Science Tutor position at xAI. With a PhD in Geophysics and a solid track record of peer-reviewed publications, I am eager to apply my scientific expertise to the challenge of training advanced AI models. My background in analyzing complex geological data and my experience in academic teaching align perfectly with your mission to create systems that accurately understand the universe.
Throughout my career, I have developed a keen eye for detail and a commitment to technical excellence. I am particularly drawn to xAI's flat organizational structure and the opportunity to contribute directly to cutting-edge AI initiatives. I am comfortable working with specialized software to provide high-quality annotations and am excited about the prospect of refining tools that will drive innovation in Earth Science disciplines.
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Описание вакансии
About xAI
xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
ABOUT THE ROLE:
As an AI Tutor - Earth Science Specialist at xAI, you will be instrumental in enhancing our cutting-edge AI technologies by providing high-quality input and labels using specialized software. You will collaborate closely with our technical team to support the training of new AI tasks, contributing to innovative initiatives. Your responsibilities include refining annotation tools and selecting complex problems from advanced Earth Science fields to drive significant improvements in model performance. This involves gathering or providing data in text, voice, and video formats, including annotations, audio recordings, or video sessions—tasks with which you must be comfortable and eager to engage.
This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. This role is a remote position. We prefer candidates available for full-time employment, but exceptional applicants seeking part-time opportunities will also be considered (please see the bottom of this job description for more details).
RESPONSIBILITIES:
- Use proprietary software applications to provide input/labels on defined projects.
- Support and ensure the delivery of high-quality curated data.
- Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
- Interact with the technical staff to help improve the design of efficient annotation tools.
- Solve problems that help drive innovation in Earth Science disciplines by guiding AI models to enhance research in specialized areas, improving outcomes in scientific discovery and application.
- Choose problems from various fields across Earth Science disciplines that align with your specialization, where you can confidently provide detailed solutions and evaluate model responses.
- Regularly interpret, analyze, and execute tasks based on given instructions.
BASIC QUALIFICATIONS:
- Master’s or PhD in earth science, geophysics, oceanography, atmospheric science, or a highly related field.
- Expertise and specialization in an Earth Science subdomain, including but not limited to oceanography, geophysics, geochemistry, atmospheric science, geology, seismology.
- Proficiency in reading and writing, both in informal and professional English.
- Strong ability to navigate various information resources, databases, and online resources is essential.
- Outstanding communication, interpersonal, analytical, and organizational capabilities.
- Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material.
- Strong passion for and commitment to technological advancements and innovation.
PREFERRED SKILLS AND EXPERIENCE:
- Advanced expertise in earth science, as demonstrated by multiple publications, preferably with one or more first-author papers, in reputable peer-reviewed journals
- Previous AI Tutoring experience.
- Teaching experience (as a professor, teacher, or tutor).
- Experience in technical writing, journalism, or a professional writing setting.
LOCATION AND OTHER EXPECTATIONS:
- This position is based in Palo Alto, CA, or fully remote.
- The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation.
- If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time.
- We are unable to provide visa sponsorship.
- Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter.
- For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.
COMPENSATION AND BENEFITS:
US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.
Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.
xAI is an equal opportunity employer. For details on data processing, view ourRecruitment Privacy Notice.
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Навыки
- Earth Science
- Geophysics
- Oceanography
- Atmospheric Science
- Geology
- Seismology
- Technical Writing
- Data Annotation
- Research
Возможные вопросы на собеседовании
Проверка глубины научных знаний и способности выбирать релевантные задачи для обучения ИИ.
Какие наиболее сложные и актуальные проблемы в вашей узкой специализации (например, сейсмологии или океанографии) вы бы выбрали для обучения модели ИИ?
Оценка навыков разметки данных и понимания того, как качество входных данных влияет на результат модели.
Как бы вы подошли к созданию эталонного набора данных для задачи, где научные данные могут быть неоднозначными или неполными?
Проверка способности работать с техническими командами над улучшением инструментов.
Опишите ваш опыт работы с программным обеспечением для анализа данных. Какие функции в инструментах аннотирования вы считаете критически важными для ученых?
Оценка навыков коммуникации и способности объяснять сложные концепции простым языком.
Представьте, что модель выдала научно неверный ответ. Как бы вы составили инструкцию для исправления этой ошибки, чтобы ИИ «понял» логику?
Проверка мотивации и готовности к специфике работы в xAI.
Почему вы решили перейти из академической среды или традиционных исследований в сферу обучения ИИ?
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