Senior Software Engineer, AI Frameworks

Details

We are seeking a Senior Software Engineer to drive integration of the NVIDIA Grove project within Dynamo and across leading open-source AI frameworks. The role focuses on developing production-grade software that enables Grove capabilities to be adopted, scaled, and operated across environments such as Dynamo, llm-d, Ray, PyTorch, and other emerging AI ecosystem frameworks. You will collaborate with engineering teams and the open-source community to deliver robust integrations, reference implementations, and developer-focused tooling.

Responsibilities

• Design and implement end-to-end integrations of Grove with open-source AI frameworks, including Dynamo, llm-d, Ray, PyTorch, and related ecosystem projects.
• Build and maintain adapters, plugins, operators, and runtime components that enable Grove features to work 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 applications, and best-practice guides to accelerate adoption by users and partners.
• Optimize performance, scalability, and reliability for distributed training and inference, including multi-node and multi-GPU environments.
• Improve observability and operational readiness through metrics, logging, tracing, and debugging tools for Kubernetes-based deployments.
• Participate in technical design reviews, define APIs and contracts, and ensure compatibility across framework and dependency versions.
• Diagnose complex issues involving containers, networking, scheduling, CUDA/GPU utilization, and framework runtime behavior.

Requirements

• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
• At least 5 years of experience in a related field.
• Hands-on experience integrating with at least one major AI framework or runtime, such as PyTorch, Ray, the Triton Inference Server ecosystem, distributed runtimes, or model-serving stacks.
• Solid understanding of AI workloads, including model development basics, training versus inference trade-offs, throughput, latency, batching, and memory considerations.
• Experience with distributed systems concepts, including RPC, scheduling, fault tolerance, and resource management.
• Practical Kubernetes experience, including deploying and operating services and jobs, Helm/Kustomize, operators/controllers, and cluster debugging.
• Familiarity with containers and cloud-native tooling, including Docker, container registries, and CI/CD pipelines.
• Strong software engineering experience in Go, C++, and/or Python, with a track record of shipping reliable systems.
• Strong interpersonal, collaboration, communication, and documentation skills, including the ability to work with open-source communities.

Preferred Qualifications

• Open-source contributions to Dynamo, PyTorch, Ray, llm-d, the Kubernetes ecosystem, or related machine-learning 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 using Nsight tools or similar technologies, and/or kernel-level performance tuning.
• Experience with reproducibility, packaging, versioning, and compatibility testing across fast-moving dependencies.

Compensation and Benefits

• Base salary range: $152,000–$241,500 for Level 3, or $184,000–$287,500 for Level 4, determined by location, experience, and pay for similar positions.
• Eligible for equity and benefits.
• Applications will be accepted at least until September 24, 2026.
• NVIDIA is an equal opportunity employer committed to an inclusive work environment.