Member of Technical Staff, Staff Physicist, Quantum Information and AI

About FirstPrinciples

FirstPrinciples is a non-profit organization building an autonomous AI Physicist to understand the nature of reality: the underlying structure, governing principles, and fundamental laws of our universe. We're developing an intelligent system that can explore theoretical frameworks, reason across disciplines, and generate novel insights to tackle the deepest unsolved problems in physics. By combining AI, symbolic reasoning, and autonomous research capabilities, we're developing a platform that goes beyond analyzing existing knowledge to actively contribute to physics research. Our goal is to accelerate progress on the questions that have captivated humanity for centuries.

We operate as a global nonprofit organization, with a Canadian foundation, a US-based 501(c)(3).

Job Description

We are looking for a Member of Technical Staff, Staff Physicist to help build an AI Physicist at the frontier of Quantum Information and AI. You will bring expertise in quantum information theory to help with training, evaluation methods, and set research direction for a rapidly evolving scientific system. This is a researcher role at the intersection of AI and physics: you will help invent new benchmarks, metrics, and evaluation methodologies for what it means to do high-quality research in Quantum Information with AI in the loop. You will work closely with research and engineering teams, and your contributions will flow straight into production model improvements and publishable outcomes.

Key Responsibilities

Scientific Critique and Research Guidance

• Review and critique model reasoning in quantum information and adjacent theory (e.g., quantum error correction, cryptography, algorithms, etc.).
• Identify subtle conceptual errors, missing assumptions, invalid proof steps, and "sounds right" failures.
• Provide clear corrections, alternative derivations, and minimal counterexamples that teach the system what good physics looks like.
• Translate domain judgment into actionable research recommendations for model behavior, reasoning style, and tool use.
• Create gold-standard demonstrations and reference solutions suitable for training and fine-tuning.
• Provide structured preferences and rankings over candidate model outputs to improve scientific reasoning quality using expert feedback loops.

Collaborators Program and Cross Functional Coordination

• Work to help us build our Collaborators program, an external group of expert peers acting like a set of reviewers.
• Coordinate review cycles and incorporate collaborator feedback into training priorities, benchmark design, and evaluation criteria.
• Align external reviewer standards with internal research goals and engineering constraints, ensuring fast iteration while maintaining scientific defensibility.
• Communicate progress and open questions clearly across collaborators, research, and engineering.

Research Output and Publication

• Help drive the system to produce outputs you would be proud to put your name on.
• Contribute to open-science artifacts where appropriate (benchmarks, datasets, technical reports, preprints).

Qualifications

• Educational Background: PhD in Physics, Quantum Information, Theoretical CS, or closely related field, plus postdoctoral-level research maturity.
• Experience: Demonstrated ability