Jobs at Modular

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 evolve MAX Framework APIs and developer experience for AI inference and training. Design scalable APIs, programming models, distributed execution primitives, and developer-facing abstractions across Python and Mojo-adjacent surfaces. Lead RFCs and technical specifications, build reference implementations, establish API quality standards, and collaborate with compiler, runtime, kernels, serving, documentation, and DevRel teams.

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.

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.

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

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.

Profile customer LLM inference workloads end-to-end and apply optimizations across GPU kernels, inference engine, and distributed systems. Build tooling and a repeatable automated optimization platform, partner with GTM and engineering to deploy tuned inference in production, and publish technical insights to shape industry best practices.

Act as the primary technical community expert for Mojo and MAX: answer complex questions, triage GitHub issues/PRs, shape open source and packaging strategy, surface product feedback to engineering, and represent Modular at events to grow and support the developer ecosystem.

Design, build, and maintain developer tooling for the MAX AI inference stack, including profilers, tracers, debuggers, dashboards, and agent-native tools. Integrate tooling across MAX, Mojo, and driver APIs, collaborate with kernel/model/serving engineers, and drive performance analysis, debugging, and observability to improve developer productivity and production reliability.