AI/ML Compiler & Runtime Software Engineer
On-site · Bengaluru, Karnataka, India or Pune, Maharashtra, India
Job Summary
Sr Staff Engineer in AI/ML compiler and runtime software for AI SDK on RISC-V platforms. Architect, design, and develop AI/ML compiler and runtime software for RISC-V IP, NPU, and SoC platforms; develop IREE-based compiler flows; create MLIR dialects and passes; enable lowering through torch-mlir, TOSA, Linalg, and related MLIR dialects; optimize neural network workloads for edge deployment; balance latency, throughput, memory, and power; collaborate with architecture, hardware, firmware, FPGA, validation, and product teams; build test infrastructure, validation flows, benchmark suites, and CI pipelines; provide technical leadership to engineers; support software enablement and deployment of AI workloads on target platforms; requires 3-12 years of hands-on software engineering; strong experience with IREE, LLVM, MLIR; experience with PyTorch/ONNX/TFLite; understanding of quantization, memory optimization, and accelerator integration; knowledge of hardware-software co-design and distributed development environments; familiarity with CI/CD tooling and customer-facing enablement; location in Pune/Bangalore, India.
Required Qualifications
- Strong hands-on experience with IREE, LLVM, and MLIR compiler infrastructure
- Experience developing MLIR dialects, compiler passes, lowering pipelines, pattern rewrites, code generation flows, or backend integration for custom hardware
- Strong C/C++ programming skills, with Python scripting for tooling
- Experience working in Linux development environments, cross-compilation, debugging, profiling, build systems, and runtime bring-up
- Experience with AI model formats and frameworks such as PyTorch, ONNX, TensorFlow Lite/TFLite
- Familiarity with RISC-V Vector, matrix acceleration concepts, custom instructions, or accelerator-specific code generation
- Experience enabling or optimizing workloads for AI accelerators, NPUs, DSPs, vector processors, matrix engines, or custom SoC IP
- Excellent communication and interpersonal skills
- Ability to lead complex software modules and mentor engineers
- Experience with edge AI deployment on real devices, boards, FPGA platforms, emulators, simulators, or early silicon
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