[Remote] Mojo Libraries Engineer

Descrição da Vaga

Requisitos

• Experience with GPU programming languages like CUDA or OpenCL
• Deep understanding of GPU architecture (memory hierarchies, tensor cores, etc.) and how it influences algorithm and API design
• Proficiency in modern systems languages (C++, Rust, or Swift), with strong skills in low-level programming, performance optimization, and memory management
• Passion for both library design and performance, with a commitment to following modern API patterns and language evolution in C++, Rust, and Swift ecosystems
• Hands-on open source experience — either through meaningful contributions or by maintaining and reviewing community submissions
• A collaborative mindset, intellectual curiosity, and drive to solve complex technical challenges as part of a high-performing team
• Strong alignment with Modular's cultural values and enthusiasm for building a thoughtful, inclusive engineering culture
• Familiarity with GPU assembly languages such as PTX and SASS
• Knowledge of cutting-edge APIs such as CUTLASS or Triton
• Prior experience with Mojo, especially with accepted contributions to the Mojo Standard Library
• Familiarity with LLVM, MLIR, or Python, particularly in systems or compiler-related contexts
• An advanced degree in Computer Science or a related field

Responsabilidades

• As a Mojo Libraries Engineer, you will design and implement core abstractions for the Mojo programming language, enabling developers to efficiently build and optimize AI systems
• Partner with teams across Modular—including compiler, kernel, and runtime engineers—to design APIs that are ergonomic, expressive, and performance-conscious
• Your work will directly shape the developer experience and deliver high business impact by enabling critical customer workloads and accelerating platform adoption
• Design and implement abstractions that enable the development and optimization of kernels and algorithms running on GPUs and CPUs, delivering top-tier performance and accuracy throughout the GenAI inference solution stack
• Optimize library functionality for performance, memory efficiency, and hardware utilization
• Participate in design discussions and code reviews to uphold high engineering standards
• Collaborate with other engineering teams to align the standard library with broader platform needs
• Contribute to a fully open source project — everything you build will be public and part of our GitHub repo
• Engage with the open source community to support high-quality contributions and foster a welcoming, inclusive environment

Benefícios