Senior Software Engineer, AI Frameworks

Description

The company is integrating the Grove project into Dynamo and a range of leading open-source AI frameworks, and this senior engineer role drives that work.

You will build production-grade software so Grove capabilities can be adopted, scaled and run smoothly in environments such as Dynamo, llm-d, Ray, PyTorch and other emerging AI frameworks.

You will work with engineering teams and the open-source community to deliver solid integrations, reference implementations and developer tooling.

Responsibilities

• Design and build end-to-end integrations of Grove with open-source AI frameworks such as Dynamo, llm-d, Ray, PyTorch and related projects.
• Create and maintain adapters, plugins, operators and runtime components that make Grove features work across training and inference stacks.
• Work with framework owners to upstream changes, contribute patches and keep integrations maintainable over time.
• Write reference workflows, sample apps and best-practice guides that help users and partners adopt the work.
• Improve performance, scalability and reliability for distributed training and inference, including multi-node and multi-GPU setups.
• Strengthen observability and operational readiness for Kubernetes deployments, covering metrics, logging, tracing and debugging tools.
• Take part in technical design reviews, define APIs and contracts, and keep frameworks and dependencies compatible across versions.
• Investigate complex problems spanning containers, networking, scheduling, CUDA and GPU utilization, and framework runtime behavior.

Requirements

• A BS, MS or PhD in Computer Science, Electrical Engineering or a related field, or equivalent experience.
• At least 5 years of proven 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.
• A solid grasp of AI workloads, including basic model development, training versus inference tradeoffs, and throughput, latency, batching and memory considerations.
• Understanding of distributed systems concepts such as RPC, scheduling, fault tolerance and resource management.
• Practical Kubernetes experience deploying and operating services and jobs, using Helm or Kustomize, and debugging clusters. Experience with operators or controllers is a nice-to-have.
• Familiarity with containers and cloud-native tooling, including Docker, container registries and CI/CD pipelines.
• Strong software engineering skills in Go, C++ and/or Python, with a record of shipping reliable systems.
• Strong interpersonal skills and the ability to collaborate across teams and with open-source communities.
• Excellent collaboration, communication and documentation habits.
• Nice to have: open-source contributions to Dynamo, PyTorch, Ray, llm-d, the Kubernetes ecosystem or related ML infrastructure projects.
• Nice to have: experience with large-scale model serving, distributed inference or multi-tenant AI platforms.
• Nice to have: experience building SDKs, APIs or developer tooling that makes integrations easier to use.
• Nice to have: knowledge of GPU performance profiling and optimization, such as Nsight tools, and or kernel-level performance tuning.
• Nice to have: experience with reproducibility, packaging, versioning and compatibility testing across fast-moving dependencies.

Conditions

Applications are accepted at least until November 2, 2026.

This posting is for an existing vacancy.

The company uses AI tools in its recruiting process.

The company is an equal opportunity employer and does not discriminate on protected characteristics.

Benefits

• Base salary depends on location, experience and the pay of employees in similar roles: 152,000 USD to 241,500 USD for Level 3, and 184,000 USD to 287,500 USD for Level 4.