{"schemaVersion":"jobsearcher.job.v1","id":"c079342046be83e770bfff27","url":"https://jobsearcher.com/jobs/c079342046be83e770bfff27","canonicalUrl":"https://jobsearcher.com/jobs/c079342046be83e770bfff27","title":"LLM Algorithm Engineer","description":"Menlo Park, CA · 5 days/week in office · Full-time\n\nAbout Corepass\nWe operate at the intersection of frontier model research and production-grade applied AI. Our customers are not looking for demos. They need agents that drive revenue, support underwriting decisions, and perform reliably in real business environments.\n\nWe are early, well-resourced, and moving fast.\n\nThe role\nWe are looking for a Large Language Model Algorithm Engineer to help build, fine-tune, align, optimize, and deploy large language models for real-world AI systems. This role focuses on model training, post-training, domain-specific model development, evaluation, inference optimization, and integration into agent systems.\n\nResponsibilities\n\nOwn fine-tuning, post-training, and performance optimization for large language models.\n\nBuild domain-specific LLMs, including data design, training, and evaluation.\n\nLead model alignment efforts, including SFT, DPO, RLHF, and related data strategy optimization.\n\nExplore reinforcement learning applications in large language models, including PPO, actor-critic methods, and related approaches.\n\nBuild an end-to-end model iteration loop, covering data, training, evaluation, and continuous improvement.\n\nContribute to model inference optimization, including distillation, quantization, acceleration, and deployment.\n\nSupport the practical deployment of models in agent-based systems.\n\nRequirements\n\nMaster’s degree or above in computer science, mathematics, artificial intelligence, or a related field.\n\nStrong foundation in deep learning and reinforcement learning.\n\nSolid understanding of Transformer architecture and large-scale model training workflows.\n\nExperience with LLM fine-tuning or post-training, such as SFT, DPO, or RLHF, is preferred.\n\nProficient in PyTorch and familiar with Linux and GPU-based development environments.\n\nStrong modeling ability and engineering implementation skills.\n\nStrong sense of ownership and a continuous improvement mindset.\n\nWhy Corepass\n\nFoundational work: Join an early team building both model infrastructure and applied AI products.\n\nReal product focus: We train our own models and build agents designed for production use, not demos.\n\nHigh-impact problems: Our agents are built for business-critical workflows such as lead generation and underwriting.\n\nFast execution: We are a tight team with low bureaucracy and a strong bias toward shipping.\n\nIn-person culture: We work from our SF Bay Area office five days a week.\n\nCorepass is an equal opportunity employer. We hire on merit and welcome candidates of every background.\n\n#J-18808-Ljbffr","company":"Corepass","rawCompany":"corepass","city":"Menlo Park","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-13T03:23:24.854Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"LLM Algorithm Engineer","description":"Menlo Park, CA · 5 days/week in office · Full-time\n\nAbout Corepass\nWe operate at the intersection of frontier model research and production-grade applied AI. Our customers are not looking for demos. They need agents that drive revenue, support underwriting decisions, and perform reliably in real business environments.\n\nWe are early, well-resourced, and moving fast.\n\nThe role\nWe are looking for a Large Language Model Algorithm Engineer to help build, fine-tune, align, optimize, and deploy large language models for real-world AI systems. This role focuses on model training, post-training, domain-specific model development, evaluation, inference optimization, and integration into agent systems.\n\nResponsibilities\n\nOwn fine-tuning, post-training, and performance optimization for large language models.\n\nBuild domain-specific LLMs, including data design, training, and evaluation.\n\nLead model alignment efforts, including SFT, DPO, RLHF, and related data strategy optimization.\n\nExplore reinforcement learning applications in large language models, including PPO, actor-critic methods, and related approaches.\n\nBuild an end-to-end model iteration loop, covering data, training, evaluation, and continuous improvement.\n\nContribute to model inference optimization, including distillation, quantization, acceleration, and deployment.\n\nSupport the practical deployment of models in agent-based systems.\n\nRequirements\n\nMaster’s degree or above in computer science, mathematics, artificial intelligence, or a related field.\n\nStrong foundation in deep learning and reinforcement learning.\n\nSolid understanding of Transformer architecture and large-scale model training workflows.\n\nExperience with LLM fine-tuning or post-training, such as SFT, DPO, or RLHF, is preferred.\n\nProficient in PyTorch and familiar with Linux and GPU-based development environments.\n\nStrong modeling ability and engineering implementation skills.\n\nStrong sense of ownership and a continuous improvement mindset.\n\nWhy Corepass\n\nFoundational work: Join an early team building both model infrastructure and applied AI products.\n\nReal product focus: We train our own models and build agents designed for production use, not demos.\n\nHigh-impact problems: Our agents are built for business-critical workflows such as lead generation and underwriting.\n\nFast execution: We are a tight team with low bureaucracy and a strong bias toward shipping.\n\nIn-person culture: We work from our SF Bay Area office five days a week.\n\nCorepass is an equal opportunity employer. We hire on merit and welcome candidates of every background.\n\n#J-18808-Ljbffr","datePosted":"2026-08-13T03:23:24.854Z","dateModified":"2026-08-13T03:23:24.854Z","hiringOrganization":{"@type":"Organization","name":"Corepass","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c079342046be83e770bfff27"},"url":"https://jobsearcher.com/jobs/c079342046be83e770bfff27"}}