{"schemaVersion":"jobsearcher.job.v1","id":"155bad50e04ccdb34cc8e190","url":"https://jobsearcher.com/jobs/155bad50e04ccdb34cc8e190","canonicalUrl":"https://jobsearcher.com/jobs/155bad50e04ccdb34cc8e190","title":"Senior Manager, Software Engineering - RL Post-Training Frameworks","description":"Overview\nLead the RL post-training frameworks strategy and team at NVIDIA, shaping an open-source ecosystem for researchers and builders. Drive cross-functional integration across training, inference, rollout, and orchestration on NVIDIA platforms, delivering durable, upstream improvements. Build and mentor a high-impact organization across US/APAC, balancing customer needs, ecosystem leverage, and technical feasibility. Enable scalable, reliable RL workloads on GPUs and NVIDIA infrastructure, with a focus on measurable impact and collaboration with open-source communities.\n\nCompensation / Benefitsequitybenefitsremote/hybrid optionscompetitive base salaryopportunity to influence open-source RL ecosystemcareer growth and leadership development\nResponsibilitiesDefine and own the RL post-training frameworks strategy and prioritization based on customer impact and ecosystem leverageEvaluate architecture and performance across training, inference, rollout, orchestration, and NVIDIA platform integrationsConverge on integrations to improve framework quality and user value; translate decisions into execution plans with milestonesLead benchmarking and reproducibility efforts; ensure delivery across open-source frameworks and distributed runtimesPartner with product management, research, DevRel, hardware, CUDA, networking, math libraries, compilers, and external collaboratorsRecruit, develop managers and senior ICs; establish US/APAC operating model and clear ownership/decision rightsCoach engineers for impactful upstream contributions in open-source ecosystemsTranslate open questions into concrete, measurable actions; set delivery goals and maintain quality barAim for durable, scalable improvements that improve RL workloads on NVIDIA systems\nKey requirements10+ years software engineering in distributed systems, AI frameworks, ML infrastructure, HPC, or systems software4+ years as an engineering manager for software teamsStrong background in distributed AI systems and end-to-end performance analysisExperience defining domain-level strategy, build-vs-buy or upstream-vs-internal decisionsAbility to drive work across organizational boundaries and communicate tradeoffs to senior leadersExperience hiring and leading engineering teams and creating staffing plansExperience establishing workflows, success metrics, and decision gates for cross-team executionExperience collaborating with open-source communities, research teams, external partners, or customer-facing teamscross-functional collaborationinfluence without authoritystrategic thinkingdistributed AI systemsRL post-training frameworks or algorithms (RLHF, PPO, GRPO, DPO, reward modeling; VeRL, Miles, Slime, SkyRL, TorchTitan)runtime and orchestration systems (Ray, Monarch, Kubernetes, Slurm)","company":"NVIDIA","rawCompany":"nvidia","city":"Seattle","state":"WA","isRemote":false,"isActive":false,"createdAt":"2026-09-15T05:16:33.037Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"11-3021.00","title":"Computer and Information Systems Managers","slug":"computer-and-information-systems-managers"}],"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":"Senior Manager, Software Engineering - RL Post-Training Frameworks","description":"Overview\nLead the RL post-training frameworks strategy and team at NVIDIA, shaping an open-source ecosystem for researchers and builders. Drive cross-functional integration across training, inference, rollout, and orchestration on NVIDIA platforms, delivering durable, upstream improvements. Build and mentor a high-impact organization across US/APAC, balancing customer needs, ecosystem leverage, and technical feasibility. Enable scalable, reliable RL workloads on GPUs and NVIDIA infrastructure, with a focus on measurable impact and collaboration with open-source communities.\n\nCompensation / Benefitsequitybenefitsremote/hybrid optionscompetitive base salaryopportunity to influence open-source RL ecosystemcareer growth and leadership development\nResponsibilitiesDefine and own the RL post-training frameworks strategy and prioritization based on customer impact and ecosystem leverageEvaluate architecture and performance across training, inference, rollout, orchestration, and NVIDIA platform integrationsConverge on integrations to improve framework quality and user value; translate decisions into execution plans with milestonesLead benchmarking and reproducibility efforts; ensure delivery across open-source frameworks and distributed runtimesPartner with product management, research, DevRel, hardware, CUDA, networking, math libraries, compilers, and external collaboratorsRecruit, develop managers and senior ICs; establish US/APAC operating model and clear ownership/decision rightsCoach engineers for impactful upstream contributions in open-source ecosystemsTranslate open questions into concrete, measurable actions; set delivery goals and maintain quality barAim for durable, scalable improvements that improve RL workloads on NVIDIA systems\nKey requirements10+ years software engineering in distributed systems, AI frameworks, ML infrastructure, HPC, or systems software4+ years as an engineering manager for software teamsStrong background in distributed AI systems and end-to-end performance analysisExperience defining domain-level strategy, build-vs-buy or upstream-vs-internal decisionsAbility to drive work across organizational boundaries and communicate tradeoffs to senior leadersExperience hiring and leading engineering teams and creating staffing plansExperience establishing workflows, success metrics, and decision gates for cross-team executionExperience collaborating with open-source communities, research teams, external partners, or customer-facing teamscross-functional collaborationinfluence without authoritystrategic thinkingdistributed AI systemsRL post-training frameworks or algorithms (RLHF, PPO, GRPO, DPO, reward modeling; VeRL, Miles, Slime, SkyRL, TorchTitan)runtime and orchestration systems (Ray, Monarch, Kubernetes, Slurm)","datePosted":"2026-09-15T05:16:33.037Z","dateModified":"2026-09-15T05:16:33.037Z","hiringOrganization":{"@type":"Organization","name":"NVIDIA","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle","addressRegion":"WA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"155bad50e04ccdb34cc8e190"},"url":"https://jobsearcher.com/jobs/155bad50e04ccdb34cc8e190"}}