> Markdown version of [/jobs/ext/4632848-senior-manager-software-engineering-rl-post-training-frameworks](https://www.wearedevelopers.com/jobs/ext/4632848-senior-manager-software-engineering-rl-post-training-frameworks). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Manager, Software Engineering - RL Post-Training Frameworks - **Company:** NVIDIA Ltd. - **Location:** Washington, DC, United States - **Experience:** Expert - **Salary:** $272,000 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Nvidia CUDA, Computer Engineering, Microprocessors, Distributed Systems, Fault Tolerance, Open Source Technology, Software Engineering, Reinforcement Learning, Graphics Processing Unit (GPU), High Performance Computing, Large Language Models, cuDNN, Kubernetes, Information Technology, SGLang, Slurm, Machine Learning Operations, TensorRT, Megatron - **Published:** November 8, 2026 - **Apply:** https://www.juju.com/job/28_25304_f1a6d2ecb4915a8deedaf04ec1b6d84d ## About the Role * MS or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience) * 10+ years of software engineering experience in distributed systems, AI frameworks, ML infrastructure, high-performance computing, or systems software, with 4+ years as an engineering manager for software teams * Strong technical background in distributed AI systems, including the ability to reason across training, inference, orchestration, and end-to-end performance, and challenge architecture and performance tradeoffs with senior engineers * Experience defining domain-level technical strategy, making build-vs-buy or upstream-vs-internal investment decisions, and creating multi-team execution plans * Ability to drive engineering work across organizational boundaries, influence without direct authority, and communicate tradeoffs clearly to senior leaders and executives * Experience hiring and leading engineering teams, developing technical leaders or new managers, and creating staffing plans for constantly evolving technical domains * Experience establishing workflows, success criteria, metrics, or decision gates that improve engineering execution across teams * Background collaborating with open-source communities, research teams, external partners, or customer-facing teams Ways To Stand Out From The Crowd * Hands-on experience with RL post-training frameworks or algorithms such as RLHF, PPO, GRPO, DPO, reward modeling, VeRL, Miles, Slime, SkyRL, OpenRLHF, NeMo-Aligner, or TorchTitan * Background with runtime and orchestration systems such as Ray, Monarch, Kubernetes, Slurm, or comparable actor-and-task-based systems * Experience scaling workloads across thousands of GPUs or heterogeneous systems, including fault tolerance, elastic recovery, stragglers, resource contention, or benchmark reproducibility * Familiarity with NVIDIA platform components such as CUDA, NCCL, cuDNN, TensorRT-LLM, Transformer Engine, Nsight, NeMo, or Megatron-Core * Demonstrated ability to turn customer or partner needs into reusable upstream improvements rather than one-off support ## Description Can you bring together globally distributed teams and the systems they build into a production-quality reinforcement learning ecosystem for researchers and model builders? Reinforcement learning post-training is where modern AI systems learn to reason, use tools, follow detailed instructions, and act as agents. Making that capability work at scale creates one of the most demanding systems problems in AI: a single RL run ties together inference, rollout, reward and critic evaluation, and training. At frontier scale, these loops have to run reliably across GPUs, CPUs, networking, storage, and open-source runtimes. You will lead the work to build, extend, and harden the rapidly evolving pieces to compose cleanly and scale with the most ambitious RL projects on NVIDIA's platforms., To meet that challenge, NVIDIA is building an RL Frameworks engineering team for the open-source tools and infrastructure that researchers, model builders, and external partners depend on. We are looking for a Senior Software Engineering Manager to set strategy, build the team, and convert emerging technical, customer, and partner signals into clear engineering priorities. The role spans RL frameworks such as VeRL, Miles, Slime, SkyRL, TorchTitan, and related post-training stacks, along with the systems those stacks build on and compose with: Megatron-Core, Ray, Monarch, NIXL, SGLang, Kubernetes, and NVIDIA platform libraries. Come build the ecosystem that the next generation of AI will rely on!