Internship
Art of Problem Solving
501-1,000 employees
Advanced math education for motivated students
Compensation Overview
$30/hr
San Diego, CA, USA
Based at headquarters in San Diego, CA; open to remote candidates from specified states.
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- Proficiency with Facebook and Instagram; experience with other platforms is a plus.
- Strong written and verbal communication skills.
- A passion for math and the ability to create content that reflects this enthusiasm.
- Creative thinker with the ability to generate new ideas for engaging content.
- Detail-oriented with strong organizational and time management skills.
- Ability to work independently and meet deadlines.
- Create and schedule engaging content on Facebook, Instagram, and other platforms using a tool like Sprout Social.
- Assist in developing and implementing social media strategies to increase brand awareness and audience engagement.
- Collaborate with our team to brainstorm and create math and education-related content that is both educational and entertaining.
- Analyze social media performance metrics and provide insights for improvement.
- Stay up-to-date with social media trends and best practices to ensure our content remains fresh and relevant.
Art of Problem Solving (AoPS) specializes in advanced math education for middle and high school students, offering online classes, textbooks, and math games that cover topics from prealgebra to calculus. The company targets motivated students who want to excel in mathematics and prepares them for competitive exams and STEM careers. AoPS stands out by providing challenging content and problem-solving skills, catering to both individual learners and educational institutions. Its goal is to enhance students' mathematical abilities and provide high-quality resources for their educational journey.
Company Size
501-1,000
Company Stage
N/A
Total Funding
N/A
Headquarters
San Diego, California
Founded
2003
Simplify's Take
What believers are saying
- New leadership could drive strategic innovations in advanced math and STEM education.
- Open-source AI models like Light-R1-32B can enhance AoPS's curriculum at low costs.
- Increased interest in AI-driven tools offers opportunities for enhanced visual problem-solving.
What critics are saying
- Free AI models like Gemini 2.0 could pressure AoPS to lower prices.
- OpenAI's image-reasoning models may attract students away from AoPS's text-based resources.
- Low-cost AI models challenge AoPS's value proposition against free alternatives.
What makes Art of Problem Solving unique
- AoPS specializes in advanced math education for grades 5-12, unlike standard curricula.
- The company offers Olympiad-level courses, setting it apart from typical math programs.
- AoPS provides both math and computer science classes, broadening its educational scope.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
401(k) Retirement Plan
401(k) Company Match
Paid Vacation
Relocation Assistance
Flexible Work Hours
Hybrid Work Options
Performance Bonus
Company News
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Google has launched Gemini 2.5 Flash, a major upgrade to its AI lineup that gives businesses and developers unprecedented control over how much “thinking” their AI performs. The new model, released today in preview through Google AI Studio and Vertex AI, represents a strategic effort to deliver improved reasoning capabilities while maintaining competitive pricing in the increasingly crowded AI market.The model introduces what Google calls a “thinking budget” — a mechanism that allows developers to specify how much computational power should be allocated to reasoning through complex problems before generating a response. This approach aims to address a fundamental tension in today’s AI marketplace: more sophisticated reasoning typically comes at the cost of higher latency and pricing.“We know cost and latency matter for a number of developer use cases, and so we want to offer developers the flexibility to adapt the amount of the thinking the model does, depending on their needs,” said Tulsee Doshi, Product Director for Gemini Models at Google DeepMind, in an exclusive interview with VentureBeat.This flexibility reveals Google’s pragmatic approach to AI deployment as the technology increasingly becomes embedded in business applications where cost predictability is essential. By allowing the thinking capability to be turned on or off, Google has created what it calls its “first fully hybrid reasoning model.”Pay only for the brainpower you need: Inside Google’s new AI pricing modelThe new pricing structure highlights the cost of reasoning in today’s AI systems
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreOpenAI launched two groundbreaking AI models today that can reason with images and use tools independently, representing what experts call a step change in artificial intelligence capabilities.The San Francisco-based company introduced o3 and o4-mini, the latest in its “o-series” of reasoning models, which it claims are its most intelligent and capable models to date. These systems can integrate images directly into their reasoning process, search the web, run code, analyze files, and even generate images within a single task flow.“There are some models that feel like a qualitative step into the future. GPT-4 was one of those. Today is also going to be one of those days,” said Greg Brockman, OpenAI’s president, during a press conference announcing the release. “These are the first models where top scientists tell us they produce legitimately good and useful novel ideas.”How OpenAI’s new models ‘think with images’ to transform visual problem-solvingThe most striking feature of these new models is their ability to “think with images” — not just see them, but manipulate and reason about them as part of their problem-solving process.“They don’t just see an image — they think with it,” OpenAI said in a statement sent to VentureBeat
SAN DIEGO, March 24, 2025 /PRNewswire/ -- Art of Problem Solving (AoPS), the leading provider of Advanced math, language arts, science, and computer science for grades 1–12, has hired Ben Kornell and Andrew Sutherland to lead the organization as CEO and Chief Product Officer, respectively. Founder and CEO Richard Rusczyk will transition to the Board on June 1, where he will join new AoPS Board members Ahmed Khaishgi and Dushyant Saraph
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. A team of researchers has introduced Light-R1-32B, a new open-source AI model optimized for solving advanced math problems, making it available on Hugging Face under a permissive Apache 2.0 license — free for enterprises and researchers to take, deploy, fine-tune or modify as they wish, even for commercial purposes. The 32-billion parameter (number of model settings) model surpasses the performance of similarly sized (and even larger) open source models such as DeepSeek-R1-Distill-Llama-70B and DeepSeek-R1-Distill-Qwen-32B on third-party benchmark the American Invitational Mathematics Examination (AIME), which contains 15 math problems designed for extremely advanced students and has an allotted time limit of 3 hours for human users.Developed by Liang Wen, Fenrui Xiao, Xin He, Yunke Cai, Qi An, Zhenyu Duan, Yimin Du, Junchen Liu, Lifu Tang, Xiaowei Lv, Haosheng Zou, Yongchao Deng, Shousheng Jia, and Xiangzheng Zhang, the model surpasses previous open-source alternatives on competitive math benchmarks.Incredibly, the researchers completed the model’s training in fewer than six hours on 12 Nvidia H800 GPUs at an estimated total cost of $1,000. This makes Light-R1-32B one of the most accessible and practical approaches for developing high-performing math-specialized AI models. However, it’s important to remember the model was trained on a variant of Alibaba’s open source Qwen 2.5-32B-Instruct, which itself is presumed to have had much higher upfront training costs.Alongside the model, the team has released its training datasets, training scripts, and evaluation tools, providing a transparent and accessible framework for building math-focused AI models.The arrival of Light-R1-32B follows other similar efforts from rivals such as Microsoft with its Orca-Math series.A new math king emergesLight-R1-32B is designed to tackle complex mathematical reasoning, particularly on the AIME (American Invitational Mathematics Examination) benchmarks
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreGoogle has quietly released a major update to its popular artificial intelligence model, Gemini, which now explains its reasoning process, sets new performance records in mathematical and scientific tasks, and offers a free alternative to OpenAI’s premium services.The new Gemini 2.0 Flash Thinking model, released Tuesday in the Google AI Studio under the experimental designation “Exp-01-21,” has achieved a 73.3% score on the American Invitational Mathematics Examination (AIME) and 74.2% on the GPQA Diamond science benchmark. These results show clear improvements over earlier AI models and demonstrate Google’s increasing strength in advanced reasoning.“We’ve been pioneering these types of planning systems for over a decade, starting with programs like AlphaGo, and it is exciting to see the powerful combination of these ideas with the most capable foundation models,” wrote Demis Hassabis, CEO of Google DeepMind, in a post on X.com (formerly Twitter).Our latest update to our Gemini 2.0 Flash Thinking model (available here: https://t.co/Rr9DvqbUdO) scores 73.3% on AIME (math) & 74.2% on GPQA Diamond (science) benchmarks. Thanks for all your feedback, this represents super fast progress from our first release just this past… pic.twitter.com/cM1gNwBoTO — Demis Hassabis (@demishassabis) January 21, 2025Gemini 2.0 Flash Thinking breaks records with million-token processingThe model’s most striking feature is its ability to process up to one million tokens of text — five times more than OpenAI’s o1 Pro model — while maintaining faster response times. This expanded context window allows the model to analyze multiple research papers or extensive datasets simultaneously, a capability that could transform how researchers and analysts work with large volumes of information.“As a first experiment, I took various religious and philosophical texts and asked Gemini 2.0 Flash Thinking to weave them together, extracting novel and unique insights,” Dan Mac, an AI researcher who tested the model, said in a post on X.com. “It processed 970,000 tokens in total