Responsibilities
- Drive development of the LLVM compiler toolchain and early software development platforms, including cycle-accurate and functional simulators. You will lead teams of engineers and technical leaders delivering large-scale projects across compiler infrastructure and simulator development
- Stay technically engaged, contributing hands-on through AI tools to evaluate the technical direction and quality across your team
- Build and mentor engineers into AI-era leaders while maintaining high engineering craft standards
- Form trusted cross-functional partnerships across software, hardware, and model teams while actively shaping strategy and roadmaps
- Drive AI adoption across teams to expand delivery capacity, improve engineering workflows, and maintain technical engagement with system architecture and code quality
Minimum Qualifications
- 5+ years of experience managing a software engineering team
- Experience with compiler architecture and development, particularly ML compilers or domain-specific languages (DSLs)
- Proven understanding and experience in executing full product life cycles (prototyping, deployment, and support)
- Experience managing engineering teams, including experience in managing other engineering leaders or technical leads
Preferred Qualifications
- Experience working closely with hardware architectures such as SIMD, GPU, RISC-V, and AI accelerators
- Experience with LLVM compiler infrastructure and MLIR
- Experience with RISC-V architecture and custom ISA tooling
- Experience in hardware-software development environments such as simulators and emulators
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Knowledge of ML frameworks like PyTorch
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Track record of driving AI-native engineering practices within an engineering organization, including integrating AI tools into development and review workflows
$219,000/year to $301,000/year + bonus + equity + benefits
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