Compiler Engineer

Compiler Engineer (GPU Backend)

Experience - 5+ Years

Key Responsibilities

• Design and implement compiler infrastructure for GPU-accelerated workloads, including lowering pipelines and code generation backends.
• Develop and optimize MLIR-based compilation passes targeting Oxmiq hardware IP and GPU architectures.
• Build and maintain LLVM backend components, including instruction selection, register allocation, and target-specific optimizations.
• Work with architecture and hardware teams to translate performance requirements into efficient code generation strategies.
• Optimize compiler output for throughput, latency, and memory efficiency across GPU workloads.
• Collaborate with kernel engineers to support Triton-based programming models and custom op lowering.
• Participate in design reviews, code reviews, and architecture discussions.
• Support performance profiling, benchmarking, and root cause analysis for compiler-generated code.

Required Qualifications

• 5+ years of compiler engineering experience with a focus on GPU or hardware accelerator backends.
• Strong expertise in C++ and LLVM, including familiarity with the LLVM IR and pass infrastructure.
• Hands-on experience with MLIR, including dialect design, conversion passes, and progressive lowering.
• Proven experience with GPU programming models, including CUDA.
• Solid understanding of code generation concepts including instruction scheduling, vectorization, and memory hierarchy optimization.
• Familiarity with GPU architecture fundamentals including thread execution models, memory systems, and occupancy constraints.
• Experience working with Triton or similar high-level GPU kernel frameworks.
• Strong debugging and performance analysis skills.
• Hands-on experience with Claude Code or equivalent AI-assisted development workflows.

Preferred Qualifications

• Experience developing compiler backends for custom AI accelerators, NPUs, or GPU IP.
• Familiarity with kernel fusion, operator tiling, and auto-tuning frameworks.
• Exposure to quantization, mixed-precision, or sparsity-aware compilation techniques.
• Experience with performance modeling and roofline analysis for GPU workloads.
• Contributions to open-source compiler projects such as LLVM, MLIR, or Triton.
• Scripting experience in Python for build automation, testing, or performance benchmarking.

Education

• BS/MS/PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field.