{"schemaVersion":"jobsearcher.job.v1","id":"71d6e6bac083bb05f9b7bd4c","url":"https://jobsearcher.com/jobs/71d6e6bac083bb05f9b7bd4c","canonicalUrl":"https://jobsearcher.com/jobs/71d6e6bac083bb05f9b7bd4c","title":"Post-Training Engineer","description":"A stealth frontier model lab is hiring a Post-Training Engineer. The company is pre-launch, sub-15 people, backed by top-tier investors, and heading toward a major general release in fall 2026. The founding team comes from OpenAI, Google Brain, and Meta FAIR. They're solving one of the hardest problems in AI: making LLMs reliable enough to build real autonomous workflows on.\n\nAbout the Role\nYou will support the core training stack with a combination of data science, creativity, and engineering, building the datasets, evals, and interventions that determine how their models behave in production.\n\nWhat You'll Do\n\nDesign and build reliable, production-grade AI systems integrating large language models and their proprietary models into real-world workflows\n\nCreate high-leverage datasets, products, and user interfaces that unlock new capabilities on top of their model\n\nRun rigorous analyses and experiments to understand how data, training choices, and targeted interventions impact model behaviour and performance\n\nDevelop and own evaluation frameworks to measure quality, reliability, and emergent characteristics across model iterations\n\nPartner with product managers and customers to translate real-world needs into concrete model and system improvements\n\nContinuously iterate and co-discover new techniques for building trustworthy, production-ready AI\n\nWho You Are\n\n5+ years of professional software engineering or equivalent expertise\n\nHave shipped user-facing products end-to-end and can name what you built and who used it\n\nStrong API coding depth, the key differentiator for this role\n\nProduct intuition: you think about how systems are used in the real world, not just technical correctness\n\nHacker/builder DNA: you build things because you want to, not because you were asked to\n\nComfortable with ambiguity; you take satisfaction in finding creative solutions\n\nHands-on experience with LLMs and a clear understanding of their capabilities and limitations\n\n#J-18808-Ljbffr","company":"Hone","rawCompany":"hone","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T03:22:08.022Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Post-Training Engineer","description":"A stealth frontier model lab is hiring a Post-Training Engineer. The company is pre-launch, sub-15 people, backed by top-tier investors, and heading toward a major general release in fall 2026. The founding team comes from OpenAI, Google Brain, and Meta FAIR. They're solving one of the hardest problems in AI: making LLMs reliable enough to build real autonomous workflows on.\n\nAbout the Role\nYou will support the core training stack with a combination of data science, creativity, and engineering, building the datasets, evals, and interventions that determine how their models behave in production.\n\nWhat You'll Do\n\nDesign and build reliable, production-grade AI systems integrating large language models and their proprietary models into real-world workflows\n\nCreate high-leverage datasets, products, and user interfaces that unlock new capabilities on top of their model\n\nRun rigorous analyses and experiments to understand how data, training choices, and targeted interventions impact model behaviour and performance\n\nDevelop and own evaluation frameworks to measure quality, reliability, and emergent characteristics across model iterations\n\nPartner with product managers and customers to translate real-world needs into concrete model and system improvements\n\nContinuously iterate and co-discover new techniques for building trustworthy, production-ready AI\n\nWho You Are\n\n5+ years of professional software engineering or equivalent expertise\n\nHave shipped user-facing products end-to-end and can name what you built and who used it\n\nStrong API coding depth, the key differentiator for this role\n\nProduct intuition: you think about how systems are used in the real world, not just technical correctness\n\nHacker/builder DNA: you build things because you want to, not because you were asked to\n\nComfortable with ambiguity; you take satisfaction in finding creative solutions\n\nHands-on experience with LLMs and a clear understanding of their capabilities and limitations\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T03:22:08.022Z","dateModified":"2026-07-16T03:22:08.022Z","hiringOrganization":{"@type":"Organization","name":"Hone","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"71d6e6bac083bb05f9b7bd4c"},"url":"https://jobsearcher.com/jobs/71d6e6bac083bb05f9b7bd4c"}}