Role/Responsibilities:
EnCharge AI is looking for an exceptional leader who can lead compiler development teams for our next generation of Edge Artificial Intelligence (AI) chips. You must have experience architecting and building compiler stacks for high-performance AI chips and a successful track record of leading large cross-functional teams building such compiler stacks.
- Use performance-driven methodologies to define a comprehensive set of compiler optimizations needed to enable high-performance AI inference solutions.
- Collaborate closely with the AI architecture, algorithms and runtime teams to create and optimize end-to-end performant AI solutions.
- Build and manage teams that enable front-end graph optimizations, back-end code generators and low-level library (kernel) development.
- Manage/Interface with teams building chip-simulators, performance models, assemblers, and disassemblers for new architectures.
- Create SDKs to interface custom compiler stack with popular AI frameworks & runtimes.
- Drive compiler roadmap features, project management and schedules.
- Work closely with the AI architecture and FPGA platform teams to jointly optimize the compiler stack and architecture - with the goal of enhancing system level performance for AI applications.
- Hire, build and lead large, cross-functional, and geographically dispersed teams.
- Mentor/lead junior engineers across the company.
Qualifications/Required Skills:
- Compiler design & computer architecture.
- D. in EE/CS with >10 years of industry experience in compiler design and/or architectures.
- >5 years of experience in AI chip compiler & library design (both R&D and products).
- Knowledge of industry-standard (and advanced) tools, graph, and intermediate-representation (IR) formats and methodologies including LLVM, MLIR and TVM.
- Familiarity with Tensorflow & PyTorch AI frameworks.
- Solid understanding of AI applications and performance bottlenecks.
- Excellent verbal and communication skills.
Preferred/Beneficial Skills:
- Proficiency with C++ and Python.
- Client engagement experience.
- Knowledge of the end-to-end runtime stack for AI applications.