Senior Manager, Software Engineering - RL Post-Training Frameworks

What you'll do

• Set strategy and priorities for RL post-training frameworks, integrations, upstream contributions, and measurable engineering execution.
• Lead architecture and performance evaluations across training, inference, rollout, orchestration, and NVIDIA platforms; establish benchmarking and reproducibility criteria.
• Build and develop globally distributed engineering teams, including managers and senior individual contributors, and coordinate delivery across organizations and partners.

What they ask for

• 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, including 4+ years as an engineering manager for software teams.
• Strong technical background in distributed AI systems, with ability to reason across training, inference, orchestration, and end-to-end performance.
• Experience setting technical strategy and execution plans, leading teams, and driving engineering work across organizational boundaries.

Nice to have

• Hands-on experience with RL post-training frameworks or algorithms, or background with runtime and orchestration systems.
• Experience scaling workloads across thousands of GPUs or heterogeneous systems; familiarity with NVIDIA platform components.

Pay

272,000 USD - 431,250 USD base salary

Tools

VeRL, Megatron-Core, Ray, Monarch, NIXL, SGLang, Kubernetes, CUDA

AI focus

Builds and scales reinforcement learning post-training frameworks and infrastructure used to train AI systems to reason, use tools, follow instructions, and act as agents.