{"schemaVersion":"jobsearcher.job.v1","id":"79651622f3b5b73987501545","url":"https://jobsearcher.com/jobs/79651622f3b5b73987501545","canonicalUrl":"https://jobsearcher.com/jobs/79651622f3b5b73987501545","title":"Software Engineer","description":"Reinforcement Learning Engineer$360,000 – $410,000 / yearAbout the roleYou'll own RL at Clippable. That means training and evaluating policies that make Clippy better at multi-step decisions: which creative to ship, when to escalate to a human, how to allocate creator budget, and how to actually learn from campaign outcomes without brittle hand-tuned rules.This is a research and production role at the same time. You'll work across our research and AI infrastructure teams, turning experiments into stable training loops and helping us decide what should be learned versus engineered.We don't care about your background or credentials. If you've shipped RL in production and can prove it, we want to talk.What you'll work onTraining policies that drive Clippy's core decisions across the marketing automation loopDesigning reward functions that capture real campaign outcomes, not proxy metricsBuilding eval harnesses that catch regressions before users doRunning offline RL and simulation-based training from logged campaign dataDeciding which behaviors we learn vs. hard-code as the product scalesWhat we're looking forRL shipped in production, not just benchmark winsHands-on experience with policy gradients, offline RL, and reward designStrong intuitions around simulation or logged-data training pipelinesAbility to move fast across research and infrastructure without losing rigorClear communicator who can help the team make tradeoffs between what to learn and what to buildNo degree, title, or years-of-experience requirement. Show us your work.Ready to apply?Apply via emailinfo@clippable.ioFull postingclippable.io/careers ↗","company":"Clippable","rawCompany":"clippable","city":"Orange","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-06-17T05:38:37.209Z","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":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer","description":"Reinforcement Learning Engineer$360,000 – $410,000 / yearAbout the roleYou'll own RL at Clippable. That means training and evaluating policies that make Clippy better at multi-step decisions: which creative to ship, when to escalate to a human, how to allocate creator budget, and how to actually learn from campaign outcomes without brittle hand-tuned rules.This is a research and production role at the same time. You'll work across our research and AI infrastructure teams, turning experiments into stable training loops and helping us decide what should be learned versus engineered.We don't care about your background or credentials. If you've shipped RL in production and can prove it, we want to talk.What you'll work onTraining policies that drive Clippy's core decisions across the marketing automation loopDesigning reward functions that capture real campaign outcomes, not proxy metricsBuilding eval harnesses that catch regressions before users doRunning offline RL and simulation-based training from logged campaign dataDeciding which behaviors we learn vs. hard-code as the product scalesWhat we're looking forRL shipped in production, not just benchmark winsHands-on experience with policy gradients, offline RL, and reward designStrong intuitions around simulation or logged-data training pipelinesAbility to move fast across research and infrastructure without losing rigorClear communicator who can help the team make tradeoffs between what to learn and what to buildNo degree, title, or years-of-experience requirement. Show us your work.Ready to apply?Apply via emailinfo@clippable.ioFull postingclippable.io/careers ↗","datePosted":"2026-06-17T05:38:37.209Z","dateModified":"2026-06-17T05:38:37.209Z","hiringOrganization":{"@type":"Organization","name":"Clippable","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Orange","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"79651622f3b5b73987501545"},"url":"https://jobsearcher.com/jobs/79651622f3b5b73987501545"}}