Senior Software Engineer, AI Frameworks

We are seeking a Senior Software Engineer to drive integration of the NVIDIA Grove project within Dynamo and across a set of leading open-source AI frameworks. In this role, you will develop production-grade software enabling Grove capabilities to be adopted, scaled, and operated smoothly. In this role, you will build production-grade software that enables seamless adoption, scaling, and operation of Grove capabilities across environments such as Dynamo, llm-d, Ray, PyTorch, and other emerging frameworks in the AI ecosystem. You will collaborate across engineering teams and the open-source community to deliver robust integrations, reference implementations, and developer-focused tooling. What you'll be doing: • Design and implement end-to-end integrations of Grove with open-source AI frameworks (e.g., Dynamo, llm-d, Ray, PyTorch, and related ecosystem projects). • Build and maintain adapters, plugins, operators, and/or runtime components that enable Grove features to work smoothly across training and inference stacks. • Partner with framework owners to upstream changes, contribute patches, and ensure long-term maintainability of integrations. • Develop reference workflows, sample apps, and best-practice guides that accelerate adoption by users and partners. • Optimize performance, scalability, and reliability for distributed training/inference, including multi-node and multi-GPU environments. • Improve observability and operational readiness (metrics, logging, tracing, debugging tools) for Kubernetes-based deployments. • Participate in technical design reviews, define APIs/contracts, and ensure compatibility across versions of frameworks and dependencies. • Diagnose complex issues spanning containers, networking, scheduling, CUDA/GPU utilization, and framework runtime behavior. What we need to see: • BS/MS/PhD in Computer Science, Electrical Engineering, or related field (or equivalent experience) • 5+ years of proven experience in related field • Hands-on experience integrating with at least one major AI framework/runtime (e.g., PyTorch, Ray, Triton Inference Server ecosystem, distributed runtimes, model serving stacks). • Solid understanding of AI workloads: model development basics, training vs. inference tradeoffs, and performance considerations (throughput/latency, batching, memory). • Experience with distributed systems concepts (RPC, scheduling, fault tolerance, resource management). • Practical Kubernetes experience: deploying and operating services/jobs, Helm/Kustomize, operators/controllers (nice to have), and debugging clusters. • Familiarity with containers and cloud-native tooling (Docker, container registries, CI/CD pipelines). • Strong software engineering experience in Go, C++ and/or Python, with a track record of shipping reliable systems. • Strong interpersonal skills and ability to collaborate across teams and with open-source communities. • Exceptional collaboration, communication, and documentation habits. Ways to stand out from the crowd: • Open-source contributions to Dynamo, PyTorch, Ray, llm-d, Kubernetes ecosystem, or related ML infrastructure projects. • Experience with large-scale model serving, distributed inference, or multi-tenant AI platforms. • Experience building SDKs/APIs or developer tooling that improves integration usability. • Knowledge of GPU performance profiling and optimization (Nsight tools or similar), and/or kernel-level performance tuning. • Experience with reproducibility, packaging, versioning, and compatibility testing across fast-moving dependencies. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and hard-working people in the world working for us. Are you creative and autono