Senior Software Engineer, CUDA Core Libraries

This is a fully remote position, open to applicants in California.

📋 Description

• Design and execute CUDA Core Libraries in C++ and/or Python, focusing on parallel algorithms and idiomatic bindings for core CUDA capabilities.

• Create, enhance, and refine GPU algorithms and APIs, from high-level interfaces to low-level performance optimization concerning memory, parallelism, and synchronization.

• Take ownership of features throughout their lifecycle: from development and implementation to testing, benchmarking, documentation, and ongoing maintenance.

• Enhance the developer experience across the entire stack: continuous integration, tests, benchmarks, packaging, examples, and documentation.

• Collaborate with senior CUDA engineers in design and code reviews, utilizing open-source-style workflows.

• Interact with actual users through issue resolution, performance analysis, and feedback on APIs.

⛳️ Requirements

• A BS, MS, or PhD in Computer Science, Computer Engineering, or a related discipline, or equivalent experience.

• A minimum of 8+ years of relevant development experience.

• Proficient programming abilities in C++, Python, or both, with a demonstrated interest in systems-level software (performance, memory, concurrency, API design).

• Strong understanding of modern C++ (templates, generics, standard library) and/or Python library development and packaging.

• Hands-on experience with parallel or heterogeneous programming (CUDA, OpenMP, GPU-accelerated Python, or similar technologies).

• Experience in contributing to production software or open-source libraries, including testing, profiling, and code review.

• Demonstrated ability to work independently, define problems, and drive projects to successful completion.

• Excellent written communication skills for technical design and documentation purposes.

• Proficient in navigating large, multi-language codebases (C++, Python, CMake, Pixi, CI systems).

🏝️ Benefits

• Equity

• Benefits