Senior/Staff Deep Learning Compiler Engineer
Quadric (company site, opens in a new tab)8+ yrsRemoteDirect career pageEst. 35–65 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design and optimize deep learning compiler stack targeting Quadric's GPNPU architecture using MLIR, Apache TVM, LLVM, etc.
- Develop lowering pathways from high-level ML frameworks (PyTorch, TensorFlow, ONNX) to optimized low-level kernel code with focus on latency, memory throughput, and power consumption.
- Collaborate with hardware teams on instruction set extensions, hardware acceleration, software simulation, FPGA/ASIC validation and hardware bring-up.
Minimum Requirements
- 8+ years experience in deep learning compiler development or related compiler infrastructure work.
- Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Computer Engineering, or related field.
- Proficient in C++ (C++14/17/20) and Python, with strong knowledge of data structures, algorithms, OOP.
- Experience with ML frameworks (PyTorch, TensorFlow, ONNX) and compiler tooling like MLIR, TVM, LLVM necessary.
Ideal Candidate Profile
- Deep expertise in deep learning compiler infrastructure and kernel-level optimization targeting AI accelerators or custom hardware.
- Experienced in hardware-software co-design involving microarchitecture collaboration and FPGA/ASIC bring-up.
- Capable of extending compiler support for novel deep learning models (Transformers, Vision Models) and delivering measurable performance improvements on benchmarks.