
11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
🔬 Science
☁️ SaaS
Artificial Intelligence • Science • SaaS
FirstPrinciples is a research company building AI systems for discovery in fundamental science. It develops domain-specialized models and tools (branded Theo: Theo Collaborator, Theo Conjecture, and Theo, the AI Physicist) to assist the scientific process—hypothesis generation, symbolic reasoning, tool integration, validation loops, and reproducible research objects. The company emphasizes transparency, stewardship of knowledge as a public good, and alignment with the scientific community. Technical claims include multiple fine-tuned models across physics domains, a model family with 120B+ parameters trained on a curated corpus of 3M+ scientific papers, and internal experiments in areas like quantum information.
🕒 July 28
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11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
🔬 Science
☁️ SaaS
Artificial Intelligence • Science • SaaS
FirstPrinciples is a research company building AI systems for discovery in fundamental science. It develops domain-specialized models and tools (branded Theo: Theo Collaborator, Theo Conjecture, and Theo, the AI Physicist) to assist the scientific process—hypothesis generation, symbolic reasoning, tool integration, validation loops, and reproducible research objects. The company emphasizes transparency, stewardship of knowledge as a public good, and alignment with the scientific community. Technical claims include multiple fine-tuned models across physics domains, a model family with 120B+ parameters trained on a curated corpus of 3M+ scientific papers, and internal experiments in areas like quantum information.
• Define a research agenda spanning near-term capabilities, reusable platforms, and field-shaping bets. • Manage, mentor, and grow researchers with strong scientific taste, technical depth, and ownership. • Fully own the business impact of research by connecting it to product, market, and user needs, setting clear milestones and maximizing the potential for projects to turn into capabilities. • Frame bold research theses and design decisive experiments, baselines, evaluations, and failure analyses. • Remain technically engaged in model development, post-training, data strategy, evaluation, and critical implementations. • Form integrated squads with engineering and domain experts from the outset of a program. • Help prototypes become reliable, reproducible, and reusable systems without losing their scientific insight. • Build compounding assets such as models, datasets, verifiers, benchmarks, simulations, agent runtimes, and research infrastructure. • Use evidence to decide when to deepen, redirect, scale, publish, protect, open-source, deploy, or conclude a line of work. • Influence broader research strategy, hiring, technical standards, infrastructure, and resource allocation.
• A strong record of original research through publications, open-source systems, deployed methods, or comparable contributions. • Experience managing researchers or providing sustained technical leadership across ambitious programs. • A PhD or equivalent research experience in machine learning, computer science, physics, mathematics, scientific computing, or a related field. • Deep expertise in at least one relevant area, with the breadth to connect it to adjacent disciplines. • Strong programming and experimental skills, including the ability to engage deeply in implementation. • A record of moving research beyond demonstrations into validated, dependable, and reusable capabilities. • Excellent judgement about novelty, evidence, technical risk, and where to place long-term bets. • The ability to build trust and alignment across research, engineering, and scientific disciplines. • A low-ego, high-agency leadership style grounded in curiosity, precision, and intellectual honesty.
• Health insurance • Professional development opportunities
Apply Now🕒 July 27
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