Principal Architect, Applied Research - Accelerator Programming Model and Compiler

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Principal Architect to define the next generation programming model for their Programmable Vision Accelerator (PVA), used in AI applications. This role involves creating higher-level abstractions and DSLs for both human developers and AI coding agents, and improving the LLVM-based compiler backend. The position requires integrating compilers with AI agents, evaluating AI-generated code, and researching efficient integration into CUDA pipelines. The role bridges research and production systems software, focusing on optimizing algorithms for PVA across NVIDIA platforms.

What you'd actually do

  1. Define the next-generation PVA programming model for developers and AI coding agents, making it easier to build optimized algorithms for PVA.
  2. Enable AI agent–driven PVA development by abstracting hardware-specific details into agent accessible, declarative interfaces, supported by improvements to compile time, emulator speed, and diagnostic tooling.
  3. Provide technical leadership for the architecture, and feature set of the PVA SDK, runtime APIs and programming model.
  4. Define benchmarks and evaluations for agent-generated PVA code and use them to improve the compiler optimizations and diagnostics.
  5. Develop and actively improve the LLVM-based VPU compiler backend targeting VLIW/SIMD architecture.

Skills

Required

  • BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent experience.
  • 15+ years of experience building high-performance, low-level systems software, accelerator software, embedded software, or compiler/toolchain infrastructure.
  • Experience building higher-level programming abstractions, DSLs or compiler IRs that abstract hardware complexity while preserving performance.
  • Experience with compiler, debugger, linker, or toolchain development, particularly using LLVM.
  • Experience developing code with agents — Claude Code, Cursor, Open AI and inference SDKs.
  • Experience integrating compilers and developer tools with AI coding agents or agentic development harnesses.
  • Experience programming SIMD/VLIW processors.
  • Excellent software development skills in C++, including low-level debugging and performance profiling.
  • Experience with Linux or QNX development environments.
  • Strong communication and social skills.

Nice to have

  • Experience with CUDA, especially integrating accelerators into a CUDA-based heterogeneous compute pipeline.
  • Background with MLIR, Halide, TVM, Triton, graph compilers, image-processing DSLs, or other declarative/compiler-based programming systems.
  • Familiarity with ISO 26262 and IEC 61508 or equivalent quality/safety standards.
  • Experience building agent harnesses and orchestrating long-running, stateful, multi-agent workflows

What the JD emphasized

  • 15+ years of experience building high-performance, low-level systems software, accelerator software, embedded software, or compiler/toolchain infrastructure.
  • Experience building higher-level programming abstractions, DSLs or compiler IRs that abstract hardware complexity while preserving performance.
  • Experience with compiler, debugger, linker, or toolchain development, particularly using LLVM.
  • Experience developing code with agents — Claude Code, Cursor, Open AI and inference SDKs.
  • Experience integrating compilers and developer tools with AI coding agents or agentic development harnesses.
  • Experience programming SIMD/VLIW processors.
  • Excellent software development skills in C++, including low-level debugging and performance profiling.

Other signals

  • AI coding agents
  • compiler backend
  • LLVM
  • SIMD/VLIW processors
  • accelerator programming