{"schemaVersion":"jobsearcher.job.v1","id":"910fe2cecca73b6d26afb0ba","url":"https://jobsearcher.com/jobs/910fe2cecca73b6d26afb0ba","canonicalUrl":"https://jobsearcher.com/jobs/910fe2cecca73b6d26afb0ba","title":"Machine Learning Engineer, Next-Generation Recommendation Systems","description":"Overview\nIn this role you will design and deploy next-generation ranking and recommendation models that leverage LLMs, RLHF, and preference learning to improve ad relevance at massive scale. You will build user understanding systems and value estimation across billions of impressions, and apply reinforcement learning to bidding and real-time ad delivery. You’ll run rigorous experiments, collaborate with engineering to productionize ideas, and clearly communicate findings to technical and non-technical stakeholders. This position sits at the frontier of research and production, contributing to Unity’s mission to power global, high-quality ad experiences at scale. You will have a direct impact on how广告\n\nCompensation / Benefitshealth, life, and disability insurancecommute subsidyemployee stock ownershipretirement/pension plansgenerous vacation and personal daysparental and family-care leave\nResponsibilitiesDesign, build, and evaluate next-generation ranking and recommendation models integrating LLMs, RLHF, and preference learningDevelop user understanding systems such as conversion prediction and behavioral modeling across billions of impressionsApply reinforcement learning and optimization techniques to bidding strategies and real-time ad deliveryDesign and run causal inference, A/B testing, and offline evaluation to measure model qualityCollaborate with engineering to productionize research across data, training, and deployed modelsCommunicate insights effectively to both technical and non-technical stakeholders\nKey requirementsPhD in Computer Science, Machine Learning, Statistics, or related fieldStrong foundations in recommendation systems, RL, LLM post-training/alignment, or related areasExperience with large-scale data and ML systemsProficiency in Python; experience with PyTorch or TensorFlowProven rigorous research output; publications at top venuesExcellent written and verbal communication skillsclear communicationcollaborationcuriosity about applied researchPyTorchTensorFlowLLMs / generative models","company":"Unity Technologies","rawCompany":"unity technologies","city":"White Plains","state":"NY","isRemote":false,"isActive":false,"createdAt":"2026-09-15T05:03:08.914Z","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":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer, Next-Generation Recommendation Systems","description":"Overview\nIn this role you will design and deploy next-generation ranking and recommendation models that leverage LLMs, RLHF, and preference learning to improve ad relevance at massive scale. You will build user understanding systems and value estimation across billions of impressions, and apply reinforcement learning to bidding and real-time ad delivery. You’ll run rigorous experiments, collaborate with engineering to productionize ideas, and clearly communicate findings to technical and non-technical stakeholders. This position sits at the frontier of research and production, contributing to Unity’s mission to power global, high-quality ad experiences at scale. You will have a direct impact on how广告\n\nCompensation / Benefitshealth, life, and disability insurancecommute subsidyemployee stock ownershipretirement/pension plansgenerous vacation and personal daysparental and family-care leave\nResponsibilitiesDesign, build, and evaluate next-generation ranking and recommendation models integrating LLMs, RLHF, and preference learningDevelop user understanding systems such as conversion prediction and behavioral modeling across billions of impressionsApply reinforcement learning and optimization techniques to bidding strategies and real-time ad deliveryDesign and run causal inference, A/B testing, and offline evaluation to measure model qualityCollaborate with engineering to productionize research across data, training, and deployed modelsCommunicate insights effectively to both technical and non-technical stakeholders\nKey requirementsPhD in Computer Science, Machine Learning, Statistics, or related fieldStrong foundations in recommendation systems, RL, LLM post-training/alignment, or related areasExperience with large-scale data and ML systemsProficiency in Python; experience with PyTorch or TensorFlowProven rigorous research output; publications at top venuesExcellent written and verbal communication skillsclear communicationcollaborationcuriosity about applied researchPyTorchTensorFlowLLMs / generative models","datePosted":"2026-09-15T05:03:08.914Z","dateModified":"2026-09-15T05:03:08.914Z","hiringOrganization":{"@type":"Organization","name":"Unity Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"White Plains","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"910fe2cecca73b6d26afb0ba"},"url":"https://jobsearcher.com/jobs/910fe2cecca73b6d26afb0ba"}}