{"schemaVersion":"jobsearcher.job.v1","id":"d7c754cd9ff2ffc4524a7ea8","url":"https://jobsearcher.com/jobs/d7c754cd9ff2ffc4524a7ea8","canonicalUrl":"https://jobsearcher.com/jobs/d7c754cd9ff2ffc4524a7ea8","title":"ML Engineer","description":"San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 5 Days Onsite\nMachine Learning Engineer\nLocation: Onsite in San Francisco\nCompensation: Competitive Salary + Equity\nWho We Are\nUniversalAGI is building OpenAI for Physics. AI startup based in San Francisco and backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Prith Banerjee (ANSYS CTO), Ion Stoica (Databricks Founder), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico). We're building foundation AI models for physics that enable end-to-end industrial automation from initial design through optimization, validation, and production. We're building a high-velocity team of relentless researchers and engineers that will define the next generation of AI for industrial engineering. If you're passionate about AI, physics, or the future of industrial innovation, we want to hear from you.\nAbout the Role\nUniversalAGI is hiring an ML Engineer to help ship ML outcomes by owning the execution layer: data preprocessing/generation, training/fine-tuning, benchmarking, and delivering results.\nWhat You’ll Do\nBuild and maintain data preprocessing and data generation pipelines to support model training and evaluation.\nRun training and fine-tuning workflows end-to-end and iterate quickly on performance improvements.\nDesign and execute benchmarking/evaluation suites to measure progress and customer outcomes.\nCollaborate with PhD expert researchers to operationalize model architectures into repeatable, production-grade workflows.\nCommunicate results clearly (metrics, dashboards, short writeups) and maintain high-quality, reproducible work.\nQualifications\nStrong software engineering skills (clean code, debugging, reliability, reproducibility).\nSolid ML foundations and hands-on experience with the ML lifecycle: data training/fine-tuning evaluation/benchmarking.\nPrior experience training or fine-tuning models (any modality/type - LLMs, computer vision, physics, surrogate models, etc.)\nOlympic athlete mindset: You have high standards for yourself and are obsessed with measurable improvement on the metrics you are delivering.\nResourcefulness: you know when to do the “quick & correct” fix vs. when to invest in a robust solution, and you can justify the tradeoff with impact/\nOwnership: Comfortable owning work end-to-end and being accountable for measurable outcomes.\nBonus Qualifications\nExperience building data pre-processing pipelines for training ML models.\nExperience with benchmarking methodology, experiment design, and metric selection.\nFamiliarity with distributed training / scalable compute workflows.\nExperience in an FDE-style / delivery execution role (or similar “ship results fast” environments).\nCultural Fit\nTechnical Respect: Ability to earn respect through hands-on technical contribution\nIntensity: Thrives in our unusually intense culture - willing to grind when needed\nCustomer Obsession: Passionate about solving real customer problems, not just publishing papers\nDeep Work: Values long, uninterrupted periods of focused work over meetings\nHigh Availability: Ready to be deeply involved whenever critical issues arise\nCommunication: Can translate complex model decisions to customers and team\nGrowth Mindset: Embraces the compounding returns of intelligence and continuous learning\nStartup Mindset: Comfortable with ambiguity, rapid change, and wearing multiple hats\nWork Ethic: Willing to put in the extra hours when needed to hit critical milestones\nTeam Player: Collaborative approach with low ego and high accountability\nBias for Action: Ships experiments fast, learns from failures, and iterates quickly\nWhat We Offer\nOpportunity to define the future of physics AI from the ground up\nWork on cutting-edge problems at the intersection of deep learning and physics simulation\nDirect collaboration with the founder & CEO and ability to influence company strategy\nCompetitive compensation with significant equity upside\nIn-person first culture - 5 days a week in office with a team that values face-to-face collaboration\nAccess to world-class investors and advisors in the AI space\nBenefits\nWe provide great benefits, including:\nCompetitive compensation and equity.\nCompetitive health, dental, vision benefits paid by the company.\n401(k) plan offering.\nFlexible vacation.\nTeam Building & Fun Activities.\nGreat scope, ownership and impact.\nAI tools stipend.\nMonthly commute stipend.\nMonthly wellness / fitness stipend.\nDaily office lunch & dinner covered by the company.\nImmigration support.\nHow We’re Different\n“The credit belongs to the man who is actually in the arena, whose face is marred by dust and\nsweat and blood; who strives valiantly; who errs, who comes short again and again... who at the\nbest knows in the end the triumph of high achievement, and who at the worst, if he fails, at least\nfails while daring greatly.\" - Teddy Roosevelt\nAt our core, we believe in being “in the arena. ” We are builders, problem solvers, and risk-takers who show up every day ready to put in the work: to sweat, to struggle, and to push past our limits. We know that real progress comes with missteps, iteration, and resilience. We embrace that journey fully knowing that daring greatly is the only way to create something truly meaningful.\nIf you're ready to train the models that will revolutionize physics simulation, push the boundaries of what AI can learn, and deliver real impact, UniversalAGI is the place for you.","company":"Universalagi","rawCompany":"universalagi","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-08-15T12:48:57.929Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"ML Engineer","description":"San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 5 Days Onsite\nMachine Learning Engineer\nLocation: Onsite in San Francisco\nCompensation: Competitive Salary + Equity\nWho We Are\nUniversalAGI is building OpenAI for Physics. AI startup based in San Francisco and backed by Elad Gil (#1 Solo VC), Eric Schmidt (former Google CEO), Prith Banerjee (ANSYS CTO), Ion Stoica (Databricks Founder), Jared Kushner (former Senior Advisor to the President), David Patterson (Turing Award Winner), and Luis Videgaray (former Foreign and Finance Minister of Mexico). We're building foundation AI models for physics that enable end-to-end industrial automation from initial design through optimization, validation, and production. We're building a high-velocity team of relentless researchers and engineers that will define the next generation of AI for industrial engineering. If you're passionate about AI, physics, or the future of industrial innovation, we want to hear from you.\nAbout the Role\nUniversalAGI is hiring an ML Engineer to help ship ML outcomes by owning the execution layer: data preprocessing/generation, training/fine-tuning, benchmarking, and delivering results.\nWhat You’ll Do\nBuild and maintain data preprocessing and data generation pipelines to support model training and evaluation.\nRun training and fine-tuning workflows end-to-end and iterate quickly on performance improvements.\nDesign and execute benchmarking/evaluation suites to measure progress and customer outcomes.\nCollaborate with PhD expert researchers to operationalize model architectures into repeatable, production-grade workflows.\nCommunicate results clearly (metrics, dashboards, short writeups) and maintain high-quality, reproducible work.\nQualifications\nStrong software engineering skills (clean code, debugging, reliability, reproducibility).\nSolid ML foundations and hands-on experience with the ML lifecycle: data training/fine-tuning evaluation/benchmarking.\nPrior experience training or fine-tuning models (any modality/type - LLMs, computer vision, physics, surrogate models, etc.)\nOlympic athlete mindset: You have high standards for yourself and are obsessed with measurable improvement on the metrics you are delivering.\nResourcefulness: you know when to do the “quick & correct” fix vs. when to invest in a robust solution, and you can justify the tradeoff with impact/\nOwnership: Comfortable owning work end-to-end and being accountable for measurable outcomes.\nBonus Qualifications\nExperience building data pre-processing pipelines for training ML models.\nExperience with benchmarking methodology, experiment design, and metric selection.\nFamiliarity with distributed training / scalable compute workflows.\nExperience in an FDE-style / delivery execution role (or similar “ship results fast” environments).\nCultural Fit\nTechnical Respect: Ability to earn respect through hands-on technical contribution\nIntensity: Thrives in our unusually intense culture - willing to grind when needed\nCustomer Obsession: Passionate about solving real customer problems, not just publishing papers\nDeep Work: Values long, uninterrupted periods of focused work over meetings\nHigh Availability: Ready to be deeply involved whenever critical issues arise\nCommunication: Can translate complex model decisions to customers and team\nGrowth Mindset: Embraces the compounding returns of intelligence and continuous learning\nStartup Mindset: Comfortable with ambiguity, rapid change, and wearing multiple hats\nWork Ethic: Willing to put in the extra hours when needed to hit critical milestones\nTeam Player: Collaborative approach with low ego and high accountability\nBias for Action: Ships experiments fast, learns from failures, and iterates quickly\nWhat We Offer\nOpportunity to define the future of physics AI from the ground up\nWork on cutting-edge problems at the intersection of deep learning and physics simulation\nDirect collaboration with the founder & CEO and ability to influence company strategy\nCompetitive compensation with significant equity upside\nIn-person first culture - 5 days a week in office with a team that values face-to-face collaboration\nAccess to world-class investors and advisors in the AI space\nBenefits\nWe provide great benefits, including:\nCompetitive compensation and equity.\nCompetitive health, dental, vision benefits paid by the company.\n401(k) plan offering.\nFlexible vacation.\nTeam Building & Fun Activities.\nGreat scope, ownership and impact.\nAI tools stipend.\nMonthly commute stipend.\nMonthly wellness / fitness stipend.\nDaily office lunch & dinner covered by the company.\nImmigration support.\nHow We’re Different\n“The credit belongs to the man who is actually in the arena, whose face is marred by dust and\nsweat and blood; who strives valiantly; who errs, who comes short again and again... who at the\nbest knows in the end the triumph of high achievement, and who at the worst, if he fails, at least\nfails while daring greatly.\" - Teddy Roosevelt\nAt our core, we believe in being “in the arena. ” We are builders, problem solvers, and risk-takers who show up every day ready to put in the work: to sweat, to struggle, and to push past our limits. We know that real progress comes with missteps, iteration, and resilience. We embrace that journey fully knowing that daring greatly is the only way to create something truly meaningful.\nIf you're ready to train the models that will revolutionize physics simulation, push the boundaries of what AI can learn, and deliver real impact, UniversalAGI is the place for you.","datePosted":"2026-08-15T12:48:57.929Z","dateModified":"2026-08-15T12:48:57.929Z","hiringOrganization":{"@type":"Organization","name":"Universalagi","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d7c754cd9ff2ffc4524a7ea8"},"url":"https://jobsearcher.com/jobs/d7c754cd9ff2ffc4524a7ea8"}}