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Build and evolve Mojo developer tooling including an LLDB-based debugger, IDE integrations, diagnostics, profiling, and GPU debugging. Partner with compiler engineers, shape roadmap, collaborate with DevRel and open-source community, and deliver production-quality debugging and developer workflows.

Lead and grow a compiler, kernel, and runtime engineering team responsible for accelerator bring-up across the Modular stack. Drive technical direction, architecture, coding, roadmap delivery, vendor partnerships, SOWs, milestones, cross-team dependencies, hiring, and production-quality model deployment across diverse hardware platforms.

As a Mojo Libraries Engineer, you'll design and implement libraries for Mojo, focusing on performance and integration with AI systems, collaborating with multiple teams to optimize algorithms and deliver high business impact.

Lead technical vision and architecture for the Mojo compiler backend: IR lowering, optimization passes, and code generation across CPUs, GPUs, and AI accelerators. Drive MLIR/LLVM initiatives, expand debugging and profiling tooling (LLDB/GDB, LSP, profilers), mentor engineers, collaborate with cross-functional teams, and engage with the open-source community to shape developer tooling and compiler strategy.

The Mojo Compiler Engineer will design and implement features for the Mojo language within an MLIR-based compiler, optimize performance for AI systems, and enhance the developer experience.

Own and scale developer community programs for Mojo and MAX, including Champions, meetups, virtual meetings, hackathons, conferences, social media, documentation, and moderation. Manage event logistics, venues, vendors, speakers, budgets, and community communications. Build scalable systems that enable community members to lead activities independently and foster peer-to-peer support among highly technical users.

Design and optimize AI runtimes across CPU and GPU hardware, improve performance through cross-stack optimization, port runtimes to new platforms, and develop benchmarking and performance-analysis systems. Collaborate with compiler, kernel, serving, model, infrastructure, tooling, and customer-success teams to support diverse AI workloads and customer requirements.

Drive the product vision for Modular's cloud compute platform, collaborating with teams to enhance AI service capabilities and customer engagement.

As a Senior AI Kernel Engineer, you will design and optimize high-performance kernels for AI inference on GPUs and custom accelerators, improving performance and collaborating with various teams to influence architecture and implementation.

Lead a team building an inference optimization platform for LLMs across GPUs and ASICs. Define technical direction, partner with GTM and engineering to tune customer workloads, create scalable optimization systems, and grow a high-impact performance engineering team.