{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/data-collection-pipeline-design"},"x-facet":{"type":"skill","slug":"data-collection-pipeline-design","display":"Data Collection Pipeline Design","count":1},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_76f61aca-ede"},"title":"Software Engineer, Human Data Interface","description":"<p><strong>About the Role</strong></p>\n<p>As a Software Engineer on Anthropic&#39;s Human Data Interfaces team, you&#39;ll own the architecture and execution of our data collection pipelines, designing systems that are both performant at scale and resilient to the rapidly changing needs of our research teams.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Architect and build data collection pipelines that support rapid iteration, balancing data quality and system maintainability</li>\n<li>Think deeply about the experience of the crowdworkers and vendors using these systems, building interfaces that are clear, efficient, and lead to high-quality data</li>\n<li>Collaborate closely with research teams to understand evolving data needs and iterate quickly on collection methods</li>\n<li>Partner with our Human Data Operations team to understand the end-to-end data workflow and design interfaces that make their jobs easier</li>\n<li>Prioritize and juggle multiple workstreams, making trade-off decisions in a fast-moving environment where research priorities can shift quickly</li>\n</ul>\n<p><strong>You May Be a Good Fit If You:</strong></p>\n<ul>\n<li>Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well</li>\n<li>Are a strong full-stack engineer with broad experience across the stack</li>\n<li>Are very good at building internal tools, including working with users of the tools to understand their needs</li>\n<li>Thrive in fast-moving environments where you need to balance speed of iteration with long-term system health</li>\n<li>Are a quick study,this team sits at the intersection of a large number of different complex technical systems that you&#39;ll need to understand (at a high level) to be effective</li>\n</ul>\n<p><strong>Strong Candidates May Also Have:</strong></p>\n<ul>\n<li>Experience building human data labelling interfaces, human-in-the-loop systems, or data collection pipelines</li>\n<li>Familiarity with how preference data and reward models are used in AI model training</li>\n<li>Experience working with researchers who are internal users/customers</li>\n<li>Background in building, and improving the user-experience of user-facing applications, particularly those involving complex UI interactions or annotation workflows</li>\n<li>Strong instincts around system design , building things that evolve gracefully as requirements change</li>\n<li>Experience influencing technical and product direction on a team</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n<li>Location-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.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;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.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive compensation and benefits</li>\n<li>Optional equity donation matching</li>\n<li>Generous vacation and parental leave</li>\n<li>Flexible working hours</li>\n<li>Lovely office space in which to collaborate with colleagues</li>\n</ul>\n<p><strong>How to Apply</strong></p>\n<p>If you&#39;re interested in this role, please submit your application through our website. We look forward to hearing from you!</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_76f61aca-ede","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5109273008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["full-stack engineering","data collection pipeline design","human data labelling interfaces","human-in-the-loop systems","data collection pipelines"],"x-skills-preferred":["preference data and reward models","AI model training","researcher collaboration","user experience design","system design"],"datePosted":"2026-04-18T15:51:03.093Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"full-stack engineering, data collection pipeline design, human data labelling interfaces, human-in-the-loop systems, data collection pipelines, preference data and reward models, AI model training, researcher collaboration, user experience design, system design","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}}]}