{"id":3589313,"url":"https://alion.io/job/firstprinciples-firstprinciples-research-fellow","title":"FirstPrinciples Research Fellow","company":{"id":6477,"name":"FirstPrinciples","domain":"firstprinciples.com","url":"https://alion.io/company/firstprinciples","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_company_offices","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["CA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":132000,"max_usd":293000,"period":"year","method":"global_role_seniority_cell","sample_n":1286},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"Reinforcement Learning","optional":false}],"status":"live","first_seen_at":"2026-11-01T12:02:03Z","employer_posted_date":null,"last_verified_at":"2026-11-01T12:02:03Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Overview:\nFirstPrinciples 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.\nWe operate as a global nonprofit organization, with a Canadian foundation, a US-based 501(c)(3).\nAs part of this effort, we are launching a Research Fellowship Program for advanced AI and physics researchers. Fellows will work directly with the FirstPrinciples Research and Engineering teams to design, test, and implement state-of-the-art (SOTA) methods and applications that will be integrated into the core AI Physicist system. This is not a paper-only fellowship and your work will go straight into production, helping shape how scientific research is performed.\nWhat You will DoAs a Research Fellow, you will own a well-scoped research direction that contributes directly to the AI Physicist's ability to reason about physics.\nCore Objectives:\nImprove Theo’s ability to produce scientifically sound, high-quality outputs in 2026;\n\nIntroduce new ideas, methods, and approaches that meaningfully shift system performance;\n\nBring deep domain expertise (PhD+ level) in one or more targeted research areas.\n\nResearch Areas & ResponsibilitiesFundamental Model Research:\n\nResearch, design, and test novel model architectures that combine academic literature, NLP, symbolic reasoning, and structured scientific workflows.\n\nPrototype and build embedding representations for physical concepts, mathematical objects, and logical structures, enabling models to reason over equations, abstractions, and scientific constraints rather than surface text alone.\n\nInvestigate alternatives to transformer-based architectures and deliver concrete recommendations.\n\nDesign and run targeted experiments to evaluate new architectural ideas, using empirical results to guide the development of next-generation model architectures.\n\nDevelop reinforcement learning loops that enable models to run internal and independent thought experiment.\n\nMultimodal Data & Benchmarking:\n\nDesign and automate scalable data ingestion pipelines that aggregate scientific literature, metadata, equations, and experimental data.\n\nCreate custom benchmarks to measure physical understanding, mathematical reasoning, and failure modes in scientific reasoning and abstraction.\n\nRefine and release curated datasets and baselines once internal validation is complete.\n\nTraining, Testing & Safety:\n\nRun and track model training jobs while managing compute usage and budget constraints.\n\nDesign sandbox environments for controlled autonomous exploration.\n\nBuild evaluation frameworks using visual and statistical tools to identify strengths and blind spots.\n\nImplement tests and guardrails that flag low-quality or unsafe outputs.\n\nMaintain internal issue tracking with clear failure modes and fixes.\n\nCollaboration & Technical Guidance:\n\nWork closely with engineers to ensure research is feasible and production-ready.\n\nCommunicate technical trade-offs clearly to non-technical stakeholders.\n\nPresent regular research updates tied to defined milestones.\n\nWho This Fellowship Is ForWe are looking for researchers who:\n\nCan operate independently and own a problem end-to-end.\n\nAre motivated by ambitious, long-horizon goals.\n\nHave strong builder instincts, not just theory.\n\nValue rigor, clarity, and intellectual honesty.\n\nAre comfortable engaging with exploratory, incomplete results.\n\nTypical profiles include:\n\nPhD or postdoctoral researchers in Computer Science, Machine Learning, Theoretical Physics, or a closely related field.\n\nTrack record of research in either:\nmodel architectures, representation learning, or reasoning systems (CS/ML path); or\n\nmathematical, physical, or formal reasoning applied to fundamental problems (physics path).\n\nDemonstrated ability to translate abstract theory into testable computational systems.\n\nComfortable working across disciplinary boundaries.\n\nProgram Structure\n6-12 month engagement with full-time or equivalent commitment\n\nFully remote\n\nFellows participate in projects and are expected to produce outputs (code, models, and other deliverables)\n\nFixed stipend for the full term\n\nHow to Express Interest:If this resonates, we welcome an expression of interest, including:\n\nResume;\n\nDescription of your research background;\n\nPrimary areas of expertise; and\n\nRelevant recent work.\n\nJoin us at FirstPrinciples and be a part of a transformative journey where science drives progress and unlocks the potential of humanity.\nOriginally posted on Himalayas","description_format":"text","description_chars":5039,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Game Design","AI Research Labs","AI for Science"],"lifecycle":[{"event":"open","at":"2026-11-01T16:15:15Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":4,"expected_fill_days":77,"reasons":["seen:4","win:early"],"computed_at":"2026-11-06T05:58:05Z"},"pay":null,"html_url":"https://alion.io/job/firstprinciples-firstprinciples-research-fellow","json_url":"https://alion.io/job/firstprinciples-firstprinciples-research-fellow.json","meta":{"generated_at":"2026-11-06T09:08:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":16534,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-07T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":6477},"rest":"https://alion.io/mcp/rest/get_company?id=6477"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ffirstprinciples-firstprinciples-research-fellow"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Ffirstprinciples-firstprinciples-research-fellow"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Ffirstprinciples-firstprinciples-research-fellow"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/firstprinciples-firstprinciples-research-fellow\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ffirstprinciples-firstprinciples-research-fellow"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3589313}},{"tool":"search_jobs","arguments":{"company":"firstprinciples.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3589313},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); 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