{"schemaVersion":"jobsearcher.job.v1","id":"b95ae5007d61e02bee91cf37","url":"https://jobsearcher.com/jobs/b95ae5007d61e02bee91cf37","canonicalUrl":"https://jobsearcher.com/jobs/b95ae5007d61e02bee91cf37","title":"Applied Scientist","description":"Most companies are building AI products on top of foundation models.\nWe’re looking for scientists who can make those models better.\nWe’re an exceptionally well-funded applied AI startup deploying frontier AI into governments, healthcare and critical industries. Rather than training foundation models from scratch, our work focuses on improving model capability through post-training, optimisation and applied machine learning—building systems that outperform off-the-shelf models on real customer problems.\nThis is a deeply technical modelling role for scientists who enjoy experimenting, measuring and improving model performance.\nThe Role You’ll own the modelling behind production AI systems.\nThat means designing experiments, improving model behaviour, building evaluation frameworks and developing novel approaches to increase capability—not simply integrating existing APIs.\nYou’ll work across areas including:\nPost-training and model adaptation\nReinforcement learning and hill-climbing optimisation\nPreference optimisation and reward modelling\nPrompt optimisation and automated search\nModel evaluation and benchmarking\nInference-time optimisation\nAgentic reasoning and planning\nMultimodal modelling\nYour work will directly determine how our AI systems perform in production.\nWhat You’ll Be Doing Develop novel modelling approaches that improve frontier model performance on complex real-world tasks\nBuild post-training pipelines that increase capability, robustness and reliability\nDesign hill-climbing and iterative optimisation algorithms to continuously improve outputs\nCreate evaluation datasets, reward functions and automated benchmarking systems\nRun large-scale experiments to understand model behaviour and identify performance gains\nPartner with engineering teams to deploy improvements into production\nTranslate cutting‑edge ML research into measurable customer impact\nWe’re Looking For We’re specifically looking for Applied Scientists who have owned the modelling , rather than engineers who have primarily built applications around existing models.\nYou’ll likely have experience with several of the following:\nDesigning or improving ML models rather than simply consuming them\nPost-training techniques including SFT, RLHF, DPO, GRPO or related optimisation methods\nReinforcement learning, hill-climbing or iterative search algorithms\nBuilding evaluation frameworks and reward models\nLLM adaptation, optimisation or fine-tuning\nStrong Python and modern ML frameworks (PyTorch, JAX or TensorFlow)\nRunning rigorous experiments and using data to drive model improvements\nWe’re particularly interested in people who enjoy asking:\n*\\\"How can we make this model perform materially better?\\\"*\nrather than:\n*\\\"How can we build an application around this model?\\\"*\nWhy Join? Work on some of the hardest applied AI modelling problems in industry\nShape how frontier models are adapted for real-world deployment\nJoin a small team of exceptional scientists and engineers with significant technical ownership\nWork with the latest frontier models, datasets and infrastructure\n$250,000–300,000 base salary plus meaningful equity\nHybrid working in San Francisco (3 days per week)\nIf you’ve built the models—not just the products around them—and enjoy pushing frontier AI beyond its default capabilities, we’d love to hear from you.\n\n#J-18808-Ljbffr","company":"Socket","rawCompany":"socket","city":"Millbrae","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-07-27T03:20:02.823Z","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":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Applied Scientist","description":"Most companies are building AI products on top of foundation models.\nWe’re looking for scientists who can make those models better.\nWe’re an exceptionally well-funded applied AI startup deploying frontier AI into governments, healthcare and critical industries. Rather than training foundation models from scratch, our work focuses on improving model capability through post-training, optimisation and applied machine learning—building systems that outperform off-the-shelf models on real customer problems.\nThis is a deeply technical modelling role for scientists who enjoy experimenting, measuring and improving model performance.\nThe Role You’ll own the modelling behind production AI systems.\nThat means designing experiments, improving model behaviour, building evaluation frameworks and developing novel approaches to increase capability—not simply integrating existing APIs.\nYou’ll work across areas including:\nPost-training and model adaptation\nReinforcement learning and hill-climbing optimisation\nPreference optimisation and reward modelling\nPrompt optimisation and automated search\nModel evaluation and benchmarking\nInference-time optimisation\nAgentic reasoning and planning\nMultimodal modelling\nYour work will directly determine how our AI systems perform in production.\nWhat You’ll Be Doing Develop novel modelling approaches that improve frontier model performance on complex real-world tasks\nBuild post-training pipelines that increase capability, robustness and reliability\nDesign hill-climbing and iterative optimisation algorithms to continuously improve outputs\nCreate evaluation datasets, reward functions and automated benchmarking systems\nRun large-scale experiments to understand model behaviour and identify performance gains\nPartner with engineering teams to deploy improvements into production\nTranslate cutting‑edge ML research into measurable customer impact\nWe’re Looking For We’re specifically looking for Applied Scientists who have owned the modelling , rather than engineers who have primarily built applications around existing models.\nYou’ll likely have experience with several of the following:\nDesigning or improving ML models rather than simply consuming them\nPost-training techniques including SFT, RLHF, DPO, GRPO or related optimisation methods\nReinforcement learning, hill-climbing or iterative search algorithms\nBuilding evaluation frameworks and reward models\nLLM adaptation, optimisation or fine-tuning\nStrong Python and modern ML frameworks (PyTorch, JAX or TensorFlow)\nRunning rigorous experiments and using data to drive model improvements\nWe’re particularly interested in people who enjoy asking:\n*\\\"How can we make this model perform materially better?\\\"*\nrather than:\n*\\\"How can we build an application around this model?\\\"*\nWhy Join? Work on some of the hardest applied AI modelling problems in industry\nShape how frontier models are adapted for real-world deployment\nJoin a small team of exceptional scientists and engineers with significant technical ownership\nWork with the latest frontier models, datasets and infrastructure\n$250,000–300,000 base salary plus meaningful equity\nHybrid working in San Francisco (3 days per week)\nIf you’ve built the models—not just the products around them—and enjoy pushing frontier AI beyond its default capabilities, we’d love to hear from you.\n\n#J-18808-Ljbffr","datePosted":"2026-07-27T03:20:02.823Z","dateModified":"2026-07-27T03:20:02.823Z","hiringOrganization":{"@type":"Organization","name":"Socket","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b95ae5007d61e02bee91cf37"},"url":"https://jobsearcher.com/jobs/b95ae5007d61e02bee91cf37"}}