EnCharge is looking for a senior software engineer (and technical lead) who can help us build out Tensor Virtual Machine (TVM) based end-to-end software runtimes for the next generation of Edge AI Hardware. You  must have a track record of building runtimes & compiler stacks for AI Inference hardware, experience with TVM, as well as strong cross-functional contributions to AI architectures & software stacks.

  • Enabling TVM support for EnCharge AI hardware, compiler, neural network operations (ops), compiler optimizations and runtime APIs.
  • Working closely with the compiler teams to define the APIs and graph exchange formats needed for TVM to connect with the EnCharge Compiler stack (to build optimized binaries). 
  • Optimizing end-to-end performance of the TVM runtime on EnCharge hardware platforms.
  • Enabling TVM backends for MLPerf benchmarking.
  • Mentor / lead junior engineers across the company.

Qualifications/Required Skills:

  • Masters/Ph.D. in EE/CS with >5 years of experience in AI applications, compilers & hardware.
  • Proficiency in C++ & Python.
  • Deep experience with modifying the TVM code base to support new hardware backends.
  • At least 3-5 years of experience with Tensorflow, PyTorch.
  • >2 years of experience with Deep Learning compilers and strong experience with AI compiler optimizations.
  • Solid understanding with state-of-the-art neural network topologies in various application domains (and especially in the computer vision space).
  • Excellent verbal and communication skills.

Preferred/Beneficial Skills:

  • Knowledge of industry-standard (and advanced) tools, graph, and intermediate-representation (IR) formats and methodologies including LLVM, MLIR etc.
  • Open-source experience.


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