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Leads developer community programs for Mojo and MAX, including Champions, meetups, virtual meetings, hackathons, conferences, social media, documentation, and moderation. Owns program strategy, event logistics, vendors, speakers, budgets, community communications, and scalable systems that enable community-led growth. Requires technical community management, advocacy program development, event operations, technical communication, and strong project execution.

Lead technical programs for Modular’s platform engineering organization, coordinating build, test, release, and continuous deployment infrastructure across compiler, runtime, kernel, cloud, and product teams. Establish planning and reporting cadences, manage dependencies and risks, define developer-experience metrics, coordinate migrations and rollouts, improve infrastructure reliability, and partner with Security on CI/CD integrity, artifact isolation, signing, provenance, and access control.

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

Champion the Mojo programming language by creating technical tutorials, blogs, videos, benchmarks, and examples; supporting developers across online communities; presenting at conferences; gathering community feedback for engineering and roadmap decisions; and collaborating with language, compiler, product, and marketing teams to grow adoption.

Developers Relations Engineer focused on MAX inference and serving. Responsibilities include benchmarking MAX against competing platforms, deploying and profiling CPU/GPU inference workloads, creating technical documentation and tutorials, supporting customer deployments, debugging community issues, presenting at technical events, and informing the product roadmap. The role requires hands-on production ML inference experience, familiarity with serving infrastructure and benchmarking methodology, strong Python and systems programming skills, and the ability to explain complex technical concepts clearly.

The role involves optimizing hardware support within a software stack for AI model deployment, collaborating with teams and hardware vendors to enhance performance and portability across platforms.

Design and implement Mojo language features, compiler optimizations, and multi-target compilation for CPUs, GPUs, and AI accelerators using MLIR and LLVM. Collaborate with kernel authors, hardware engineers, researchers, and the open-source community to improve language design, code generation, performance, developer experience, and the broader Mojo SDK.

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.