EnCharge AI is looking for an exception technical leader who can help us build out high-performance optimized libraries for our Edge AI Artificial Intelligence chips. You must have an excellent track record of building out libraries for various platforms (CPU and / or accelerator architectures) and enabling high-performance kernels in these architectures. This position is also a strong growth opportunity, with the possibility of transitioning into further leadership roles in the coming years.
- Defining the overall strategy and execution plan for core-level libraries for optimized AI Inference deployment on EnCharge Hardware.
- Work closely with the compiler team to define and execute on the primary set of optimized AI library templates (hand-written in EnCharge assembly) that’d be used for code-generation in AI Inference applications.
- Work closely with the AI Hardware, Compiler, Performance & FPGA teams to determine the performance of these AI libraries and compiled binaries and to propose microarchitecture, ISA, library & compiler changes to further improve runtime performance.
- Interface / work closely with teams building chip-simulators, performance models, assemblers, and disassemblers for the EnCharge architecture.
- Hire, build and lead large, cross-functional, and geographically dispersed teams.
- Mentor / lead junior engineers across the company.
- Masters/Ph.D. in EE/CS with >5 years of industry experience in chip-design, architecture & systems.
- Proficiency with C++, Python and Systems programming.
- Deep knowledge of architectures (and instruction-sets), microarchitectures, system design and performance optimizations.
- >5 years of experience building software libraries for various architectures.
- >3 years of experience with managing software teams.
- Solid understanding of AI Applications, kernels, and performance bottlenecks.
- Experience with building performance models and simulators for new architectures.
- Knowledge of industry-standard (and advanced) tools and methodologies.
- Excellent verbal and written communication skills.
- Knowledge of the end-to-end runtime stack for AI applications.
- Experience with CI/CD.
- Knowledge of AI Compiler stacks.