{"schemaVersion":"jobsearcher.job.v1","id":"5a0efda9ba6a185f593cab3b","url":"https://jobsearcher.com/jobs/5a0efda9ba6a185f593cab3b","canonicalUrl":"https://jobsearcher.com/jobs/5a0efda9ba6a185f593cab3b","title":"Research Engineer, Visual Knowledge Work","description":"About Anthropic\nAnthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n\nAbout the role\nWe’re looking for a research engineer who believes that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. On the Vision team, you’ll own the end‑to‑end process of creating training data and RL environments targeting visual knowledge work: identifying long‑horizon and vision‑heavy tasks, building evals, designing rewards, and scaling data. This is a unique role that combines applied research with hands‑on data work. It’s also highly collaborative — you’ll partner with external vendors, pretraining, RL, and product teams to make sure the environments you build translate into real‑world knowledge work capabilities.\n\nWhat you’ll do:\n\nOwn the data strategy for vision capabilities end‑to‑end, from building evals and scaling RL environments\n\nManage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design\n\nDevelop and improve QA frameworks that catch reward hacking and ensure environment quality at scale\n\nRun generalization experiments to measure how data strategy changes improve multimodal capabilities on held‑out evaluations\n\nPartner with pretraining, RL, and product teams, and do the science that shows we’re all rowing in the same direction\n\nYou may be a good fit if you:\n\nHave 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects\n\nHave experience with reinforcement learning, reward design, or training data curation for large language or vision‑language models\n\nAre familiar with the architecture, training, and operation of large vision language models\n\nAre comfortable managing technical vendor relationships and iterating quickly on feedback\n\nAre results‑oriented, with a bias towards flexibility and impact\n\nCare about the societal impacts of your work\n\nStrong candidates may also have experience with:\n\nDesigning evals or benchmarks for LLMs or vision language models\n\nLarge‑scale pretraining, SL, and RL on language models\n\nDeep learning research on images, video, or other modalities\n\nDeveloping complex agentic systems using LLMs\n\nLarge‑scale ETL and data pipeline development\n\nRepresentative projects:\n\nWriting a vendor‑facing specification for a new family of visual RL training tasks, then iterating with the vendor on coverage, quality, and reward design\n\nRunning experiments to determine ideal training data mixes and parameters for a synthetically generated vision dataset\n\nFinetuning Claude to maximize its performance using a particular set of agent tools/skills\n\nCompensation\nThe annual compensation range for this role is $350,000 – $850,000 USD.\n\nFor sales roles, the range provided is the role’s On Target Earnings (OTE) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n\nLogistics\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\n\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n\nLocation-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n\nVisa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n\n#J-18808-Ljbffr","company":"Anthropic","rawCompany":"anthropic","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T03:14:59.254Z","occupations":[{"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"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"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":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Research Engineer, Visual Knowledge Work","description":"About Anthropic\nAnthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n\nAbout the role\nWe’re looking for a research engineer who believes that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. On the Vision team, you’ll own the end‑to‑end process of creating training data and RL environments targeting visual knowledge work: identifying long‑horizon and vision‑heavy tasks, building evals, designing rewards, and scaling data. This is a unique role that combines applied research with hands‑on data work. It’s also highly collaborative — you’ll partner with external vendors, pretraining, RL, and product teams to make sure the environments you build translate into real‑world knowledge work capabilities.\n\nWhat you’ll do:\n\nOwn the data strategy for vision capabilities end‑to‑end, from building evals and scaling RL environments\n\nManage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design\n\nDevelop and improve QA frameworks that catch reward hacking and ensure environment quality at scale\n\nRun generalization experiments to measure how data strategy changes improve multimodal capabilities on held‑out evaluations\n\nPartner with pretraining, RL, and product teams, and do the science that shows we’re all rowing in the same direction\n\nYou may be a good fit if you:\n\nHave 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects\n\nHave experience with reinforcement learning, reward design, or training data curation for large language or vision‑language models\n\nAre familiar with the architecture, training, and operation of large vision language models\n\nAre comfortable managing technical vendor relationships and iterating quickly on feedback\n\nAre results‑oriented, with a bias towards flexibility and impact\n\nCare about the societal impacts of your work\n\nStrong candidates may also have experience with:\n\nDesigning evals or benchmarks for LLMs or vision language models\n\nLarge‑scale pretraining, SL, and RL on language models\n\nDeep learning research on images, video, or other modalities\n\nDeveloping complex agentic systems using LLMs\n\nLarge‑scale ETL and data pipeline development\n\nRepresentative projects:\n\nWriting a vendor‑facing specification for a new family of visual RL training tasks, then iterating with the vendor on coverage, quality, and reward design\n\nRunning experiments to determine ideal training data mixes and parameters for a synthetically generated vision dataset\n\nFinetuning Claude to maximize its performance using a particular set of agent tools/skills\n\nCompensation\nThe annual compensation range for this role is $350,000 – $850,000 USD.\n\nFor sales roles, the range provided is the role’s On Target Earnings (OTE) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n\nLogistics\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\n\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n\nLocation-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n\nVisa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T03:14:59.254Z","dateModified":"2026-07-16T03:14:59.254Z","hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"5a0efda9ba6a185f593cab3b"},"url":"https://jobsearcher.com/jobs/5a0efda9ba6a185f593cab3b"}}