Posted today · be early
AI Researcher
FirstPrinciples
WorldwideremotePosted 1 day ago
Skill Required
AI-ResearchMachine-Learning-ResearchResearch-ScientistNLP-EngineerData-ScienceAI-ResearcherAI-Research-ScientistResearch-AI-ScientistAI-ScientistAI-Research-SpecialistAI-ML-Research-ScientistAINLPMachine LearningDeep Learningrelated fieldEngineeringdevelopingObservabilitybuildingwrittenTestNGdesignRailsandFulltime
Key highlights
- FirstPrinciples is a global nonprofit building an autonomous AI Physicist to advance fundamental physics research, operating via a Canadian foundation and US 501(c)(3) status
- Role requires a PhD in physics, computer science, data science, information systems, or a related field
- Must have a proven track record of conducting in-depth research on scientific AI models, symbolic models, machine learning/deep learning for scientific discovery
- Work is directly integrated into production and impacts the broader academic physics community
- Key responsibilities include building custom tokenizers for LaTeX symbols and physical units, developing reinforcement learning loops for independent model thought experiments, and creating benchmarks to assess model physical concept understanding and reduce hallucinations
- Organization develops AI combining symbolic reasoning, autonomous research, and cross-disciplinary reasoning to generate novel physics insights
Role overview
FirstPrinciples is a global nonprofit organization operating via a Canadian foundation and US 501(c)(3) status, building an autonomous AI Physicist to uncover the fundamental structure, governing principles, and laws of the universe. The organization develops AI systems that combine symbolic reasoning, autonomous research capabilities, and cross-disciplinary reasoning to generate novel insights into humanity's oldest unsolved physics problems, moving beyond analyzing existing knowledge to actively contributing to cutting-edge physics research. The Member of Technical Staff, Research will investigate, design, test, and develop state-of-the-art AI methods and applications integrated into FirstPrinciples' core AI engine, collaborating with cross-functional teams to deliver production-ready solutions that advance scientific research practices and impact the broader academic community. The ideal candidate has a proven track record in AI research and can combine strategic thinking with technical depth to bring complex ideas to life.
Responsibilities
- Investigate, design, test, and develop state-of-the-art (SOTA) methods and applications integrated into FirstPrinciples' broader AI engine
- Collaborate with cross-functional teams to deliver production-ready solutions that advance scientific research practices, with work directly impacting the wider academic community to usher in a new era of scientific discovery
- Research, design, and test novel, research-specific model architectures that integrate academic literature, natural language processing (NLP), symbolic reasoning, and other methods to orchestrate the scientific process
- Prototype and build custom tokenizers for LaTeX symbols and physical units to be treated as tokens
- Explore alternatives to transformers through in-depth research and provide practical recommendations for model development
- Develop reinforcement-learning loops to enable models to run independent and internal thought experiments
- Design and automate data ingestion pipelines in collaboration with Data Scientists & Engineers that aggregates science literature, metadata, experimental data, equations, and other data sources in a robust and scalable manner
- Establish custom benchmarks to assess the models’ understanding of physical concepts, mathematical reasoning abilities, and ability to minimize hallucinations for the benefit of scientific reliability
- Refine and release datasets and baselines once internal tests are stable
- Run and track model training jobs while leading the technical team through setup, monitoring progress, and constraining costs within budget
- Develop approaches to stage "practice runs" in a sandbox environment to develop the model’s abilities to explore ideas independently while logging results for later review
- Develop a framework to evaluate the models’ learning using visual and statistical tools to spot patterns and blind spots
- Add guard-rails and tests that flag poor quality model output
- Maintain internal tools to track lists of known issues, noting failures, clear fixes, and improvements to be integrated into future development
- Work with the engineering team to ensure product feasibility and robust architecture
- Translate technical trade-offs to non-technical stakeholders in clear terms
- Present findings in clear updates to the technical team in order to keep the broader team apprised of progress against research milestones
Requirements
- PhD in physics, computer science, data science, information systems, or related field
- Proven track record of conducting in-depth research on scientific AI models, symbolic models, machine learning or deep learning for scientific discovery
- Familiarity with state-of-the-art (SOTA) models, best practices in model development processes, in-depth AI/ML concepts, and data infrastructure
- Comfort working closely with engineers and other technical team members
- Strong written and verbal communication skills
- Comfortable working in a startup-style, cross-functional, remote team
Nice to have
- Experience with or strong interest in physics and/or fundamental science topics
- Experience conducting research on AI models in an early-stage or mission-focused environment
Additional details
- Interested candidates are invited to submit their resume, a cover letter detailing their qualifications and vision for the role, and references. Please include "Member of Technical Staff, Research" in the cover letter.
- Originally posted on Himalayas
