Earth Science Tutor

xAI

SpaceXAI’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 - Space Science Specialist at SpaceXAI, 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 space 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. The AI Tutor - Space Science Specialist 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 space 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 space 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 astrophysics, astronomy, physics, or a highly related field. * Expertise and specialization in a space science subdomain, including but not limited to galactic astronomy, extragalactic astronomy, observational astronomy, stellar astrophysics, high-energy astrophysics, cosmology, planetary science, earth sciences, astroparticle physics, general relativity, and interdisciplinary space sciences. * 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 physics, astronomy, or astrophysics, 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: * Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit. * For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required.  On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.  * Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs. * For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time. * We are unable to provide visa sponsorship. * For those who will be working from a personal device, 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. SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Prior Labs

WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening, and we're hiring the team that makes it. Momentum. We pioneered tabular foundation models and are now the world-leading organization in structured-data ML. Our TabPFN v2 model was published as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi to improving clinical-trial decisions with BostonGene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team. We're a small, highly selective team of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do top-tier research, and hold each other to an extremely high bar. What's next. In 2025 we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here, which makes this an ideal time to join. ABOUT THE ROLE You'll join our data science team working with an entirely new class of AI models. As a Data Scientist at Prior Labs, you'll be the critical link between our foundation models and real-world applications — experimenting hands-on with our tabular foundation models (including TabPFN) to uncover new applications, working directly with customers to show how native tabular AI solves problems traditional methods can't, and translating what you learn back into our product roadmap. HOW YOU'LL DRIVE IMPACT: Applied Data Science & Experimentation: Identify high-impact use cases for TFMs and build proof-of-concepts that showcase their advantages over traditional ML. Develop best-practice workflows using capabilities like in-context learning (ICL) and benchmark rigorously against existing approaches. Customer Success: Work directly with users to understand their challenges and demonstrate TFM value through technical demos tied to real business objectives. Guide onboarding to deliver quick wins and translate user feedback into technical insights for our product team. Community & Education: Design and deliver workshops, tutorials, and content that explains the tabular foundation model paradigm — how it differs from LLMs and traditional ML, and why it matters. Engage the data science community through Kaggle, GitHub, and public-facing work. WHAT WE'RE LOOKING FOR: * PhD or Master's in a quantitative field, plus 3+ years of experience building and deploying ML/AI in industry, competitive ML, or open-source. * Deep proficiency in Python and the data science ecosystem, with hands-on experience training and deploying deep learning models in PyTorch, including modern deep learning - architectures (especially transformers) * Collaborative development on GitHub and strong software engineering practices * Ability to translate complex technical concepts into tangible value for both technical and non-technical audiences * Genuine curiosity about new model architectures and a drive to explore what they can do NICE TO HAVE: * Kaggle Grandmaster, Master, or Expert status * Experience in technical consulting, solutions engineering, MLOps, or developer advocacy * Contributions to open-source libraries or data science tooling * A portfolio of blog posts, talks, or projects that demonstrate strong technical communication Life at Prior Labs We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with. We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you. We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the whole company comes together regularly for offsites to think, build, and celebrate together. Our Commitments We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box." We're committed to creating a safe, inclusive environment and providing equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.

Jua

OVERVIEW Physical AI, a real model of the world, is the next trillion dollar opportunity and a foundational pillar for energy, robotics and superintelligence. At Jua we are building it now. Our models already run on four continents and help power the energy buildout needed to support ever larger intelligence. We are assembling a world-class team of researchers and entrepreneurial minds to turn this model into reality at global scale. If you want the opportunity of your life, come build physical AI with us. WHAT WE’RE LOOKING FOR We’re looking for an exceptional and ambitious Data Engineering Intern who’s eager to learn fast, take ownership, and contribute to real production systems. You’ll work together with our experienced data and AI engineers and support expanding and refining Jua’s data infrastructure, focusing on data acquisition, validation, and integration using Dagster, Python, and modern cloud technologies. Your work will directly accelerate our ability to onboard new datasets and improve model performance. Internship duration: 3 months (extendable to 6 months) RESPONSIBILITIES AND TASKS * Integrate and onboard new weather, climate, and geospatial datasets into Jua’s data infrastructure * Build and maintain robust data pipelines using Dagster, ensuring reliability and scalability * Collaborate with engineers and scientists to validate data quality, completeness, and usability * Contribute to documentation and automation that improve data ingestion and processing workflows * Support hindcast generation and other foundational data operations to increase engineering throughput * Learn directly from experienced mentors while contributing to production-grade systems that power Jua’s AI models NEED-TO-HAVE * Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computational Science, Engineering, Physics, Atmospheric or Earth Science * or a proof that you are exceptional in your field without a degree (show us your projects on Github) * Strong programming skills in Python and familiarity with Git * High intellect, curiosity, strong attention to detail, and a drive to excel in a fast-paced environment where intensity, long hours, and high standards are the norm NICE-TO-HAVE * Understanding of data pipelines, ETL processes, and workflow orchestration tools such as Dagster, Airflow, or Prefect * Basic familiarity with GCP or AWS, and experience handling structured or geospatial data * Familiarity with Docker or containerized development * Knowledge of SQL and basic data modeling concepts * Interest in machine learning or large-scale simulation systems AT THE END OF YOUR INTERNSHIP, YOU WILL HAVE * Built and deployed data pipelines used in production at Jua * Onboarded new datasets that enhance model accuracy and experimentation speed * Gained hands-on experience with Dagster, cloud infrastructure, and collaborative data workflows * Contributed directly to Jua’s mission to redefine how the world forecasts and understands the physical world * Demonstrated exceptional ownership, technical skill, and impact ABOUT YOU * You’re technically strong, curious, and eager to learn fast * You take initiative and enjoy solving open-ended problems * You thrive in an environment where expectations are high and feedback is direct * You’re excited by the idea of working with world-class engineers and scientists on real-world data challenges Please note: We prioritise your answers to the application questions over your CV, so we encourage you to complete them as thoughtfully and thoroughly as possible. At Jua, we foster a performance culture and value people who embody our beliefs of service and adventure. We prioritize agility, operating at the highest clock speed to adapt quickly to change. We innovate on behalf of our users and leverage data supremacy to maintain our competitive edge. Through clear communication and fact-based decision-making, we ensure alignment in our pursuit of excellence. With these principles, we aim to create a customer-focused, value-centric organization that sets new standards in the industry. We value the unique perspectives that each individual brings to the table and believe that embracing diverse backgrounds and experiences enriches our collective journey towards growth and success.